Datasets:
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type list<item: int64> to int64
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2152, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2016, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type list<item: int64> to int64
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
model list | dataset string | modality string | row_no int64 | features dict | target dict | predicted dict | example string | q_type int64 | q string |
|---|---|---|---|---|---|---|---|---|---|
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 21,414 | {
"age": 57,
"workclass": "Local-gov",
"fnlwgt": 44273,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Widowed",
"occupation": "Transport-moving",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 18,785 | {
"age": 61,
"workclass": "Private",
"fnlwgt": 146788,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 29,811 | {
"age": 39,
"workclass": "Private",
"fnlwgt": 174330,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Separated",
"occupation": "Craft-repair",
"relationship": "Unmarried",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-cou... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 34,486 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 27408,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 32,162 | {
"age": 30,
"workclass": "Private",
"fnlwgt": 302473,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 15,313 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 160291,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 15,176 | {
"age": 36,
"workclass": "Private",
"fnlwgt": 150057,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 45,653 | {
"age": 42,
"workclass": "Private",
"fnlwgt": 22831,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 9,800 | {
"age": 17,
"workclass": "Private",
"fnlwgt": 147069,
"education": "11th",
"education-num": 7,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 16,
"native... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 28,387 | {
"age": 33,
"workclass": "State-gov",
"fnlwgt": 174171,
"education": "Some-college",
"education-num": 10,
"marital-status": "Separated",
"occupation": "Tech-support",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 12,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 37,795 | {
"age": 40,
"workclass": "Private",
"fnlwgt": 124692,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 38,572 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 188972,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Widowed",
"occupation": "Exec-managerial",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 38,457 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 137591,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 35,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,057 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 109997,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 8,688 | {
"age": 68,
"workclass": "Self-emp-not-inc",
"fnlwgt": 150904,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Widowed",
"occupation": "Craft-repair",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 35,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 33,515 | {
"age": 57,
"workclass": "Private",
"fnlwgt": 266189,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 42,
"native-co... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 47,243 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 301862,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Unmarried",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
"native... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 45,037 | {
"age": 25,
"workclass": "Private",
"fnlwgt": 167031,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Other-relative",
"race": "Other",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week":... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 29,415 | {
"age": 41,
"workclass": "State-gov",
"fnlwgt": 180272,
"education": "Masters",
"education-num": 14,
"marital-status": "Never-married",
"occupation": "Prof-specialty",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 35,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 32,048 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 81232,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 15024,
"capital-loss": 0,
"hours-per-week": 50,
"nati... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 30,669 | {
"age": 21,
"workclass": "Private",
"fnlwgt": 179720,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Other-relative",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 26,148 | {
"age": 37,
"workclass": "Private",
"fnlwgt": 227545,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 44,
"nati... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 47,537 | {
"age": 52,
"workclass": "Self-emp-not-inc",
"fnlwgt": 34973,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Farming-fishing",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1887,
"hours-per-wee... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 40,160 | {
"age": 38,
"workclass": "State-gov",
"fnlwgt": 188303,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Protective-serv",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 7688,
"capital-loss": 0,
"hours-per-wee... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,403 | {
"age": 46,
"workclass": "Private",
"fnlwgt": 411595,
"education": "5th-6th",
"education-num": 3,
"marital-status": "Widowed",
"occupation": "Machine-op-inspct",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 27,209 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 113466,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"na... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 10,348 | {
"age": 58,
"workclass": "Private",
"fnlwgt": 141379,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 42,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 3,280 | {
"age": 18,
"workclass": "Private",
"fnlwgt": 122988,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Handlers-cleaners",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 20,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,579 | {
"age": 21,
"workclass": "Private",
"fnlwgt": 83704,
"education": "12th",
"education-num": 8,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 23,484 | {
"age": 40,
"workclass": "Self-emp-not-inc",
"fnlwgt": 238574,
"education": "Prof-school",
"education-num": 15,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-w... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 25,727 | {
"age": 28,
"workclass": "Private",
"fnlwgt": 398220,
"education": "5th-6th",
"education-num": 3,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Other-relative",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,598 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 246038,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,742 | {
"age": 41,
"workclass": "Private",
"fnlwgt": 160893,
"education": "Assoc-acdm",
"education-num": 12,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 45,... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 32,508 | {
"age": 54,
"workclass": "Private",
"fnlwgt": 210736,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,255 | {
"age": 40,
"workclass": "Self-emp-not-inc",
"fnlwgt": 145441,
"education": "Some-college",
"education-num": 10,
"marital-status": "Divorced",
"occupation": "Exec-managerial",
"relationship": "Unmarried",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 47,661 | {
"age": 47,
"workclass": "Private",
"fnlwgt": 252079,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Machine-op-inspct",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 7688,
"capital-loss": 0,
"hours-per-week":... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 13,808 | {
"age": 49,
"workclass": "Private",
"fnlwgt": 118520,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 45,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 22,639 | {
"age": 45,
"workclass": "Local-gov",
"fnlwgt": 148222,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,663 | {
"age": 47,
"workclass": "Private",
"fnlwgt": 431515,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 18,148 | {
"age": 36,
"workclass": "Federal-gov",
"fnlwgt": 128884,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 48,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 21,762 | {
"age": 19,
"workclass": "Self-emp-not-inc",
"fnlwgt": 30800,
"education": "10th",
"education-num": 6,
"marital-status": "Married-spouse-absent",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "Amer-Indian-Eskimo",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"ho... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,071 | {
"age": 47,
"workclass": "Private",
"fnlwgt": 140664,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Divorced",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 45,
"native-coun... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,213 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 520759,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 28,662 | {
"age": 44,
"workclass": "State-gov",
"fnlwgt": 691903,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 60,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 7,234 | {
"age": 40,
"workclass": "Self-emp-inc",
"fnlwgt": 115411,
"education": "Assoc-acdm",
"education-num": 12,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,284 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 341187,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 46,692 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 327779,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Handlers-cleaners",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week":... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 48,236 | {
"age": 46,
"workclass": "Local-gov",
"fnlwgt": 267952,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Divorced",
"occupation": "Exec-managerial",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 36,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,099 | {
"age": 45,
"workclass": "Local-gov",
"fnlwgt": 235431,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Separated",
"occupation": "Other-service",
"relationship": "Unmarried",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,145 | {
"age": 50,
"workclass": "State-gov",
"fnlwgt": 229272,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 23,205 | {
"age": 38,
"workclass": "Private",
"fnlwgt": 119177,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 45,406 | {
"age": 24,
"workclass": "Private",
"fnlwgt": 143766,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Machine-op-inspct",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 55... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 38,810 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 185452,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Exec-managerial",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 34,749 | {
"age": 34,
"workclass": "Private",
"fnlwgt": 209691,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 4386,
"capital-loss": 0,
"hours-per-week": 50... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,519 | {
"age": 62,
"workclass": "Private",
"fnlwgt": 113080,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Divorced",
"occupation": "Craft-repair",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-coun... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 17,704 | {
"age": 41,
"workclass": "Private",
"fnlwgt": 184102,
"education": "11th",
"education-num": 7,
"marital-status": "Divorced",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-co... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 11,716 | {
"age": 25,
"workclass": "Private",
"fnlwgt": 161631,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,725 | {
"age": 43,
"workclass": "Private",
"fnlwgt": 76460,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 609 | {
"age": 33,
"workclass": "Local-gov",
"fnlwgt": 217304,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 11,823 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 282753,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 44,599 | {
"age": 38,
"workclass": "Self-emp-not-inc",
"fnlwgt": 194534,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 99999,
"capital-loss": 0,
"hours-per-w... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,633 | {
"age": 28,
"workclass": "Private",
"fnlwgt": 207513,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 48,
"native-countr... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 17,088 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 169879,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 3103,
"capital-loss": 0,
"hours-per-week": 47... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,270 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 191324,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Protective-serv",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 25,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,112 | {
"age": 31,
"workclass": "Private",
"fnlwgt": 147284,
"education": "Doctorate",
"education-num": 16,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1977,
"hours-per-week": 99... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 4,484 | {
"age": 18,
"workclass": "Private",
"fnlwgt": 217942,
"education": "11th",
"education-num": 7,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 24,
"native-c... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 34,474 | {
"age": 52,
"workclass": "Private",
"fnlwgt": 110748,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,488 | {
"age": 64,
"workclass": "Private",
"fnlwgt": 321166,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Divorced",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 5,
"native-cou... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 40,272 | {
"age": 62,
"workclass": "Private",
"fnlwgt": 345780,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Divorced",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 37,771 | {
"age": 19,
"workclass": "Private",
"fnlwgt": 146679,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Exec-managerial",
"relationship": "Own-child",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 44,934 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 315974,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 15,970 | {
"age": 38,
"workclass": "Federal-gov",
"fnlwgt": 455379,
"education": "12th",
"education-num": 8,
"marital-status": "Married-civ-spouse",
"occupation": "Protective-serv",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 56,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 28,750 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 256764,
"education": "Assoc-acdm",
"education-num": 12,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 33,876 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 301867,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "Asian-Pac-Islander",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 12,740 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 193190,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 3,797 | {
"age": 39,
"workclass": "Private",
"fnlwgt": 346478,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-cou... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 7,814 | {
"age": 36,
"workclass": "Private",
"fnlwgt": 120204,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Tech-support",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 12,311 | {
"age": 24,
"workclass": "Private",
"fnlwgt": 88824,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Tech-support",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 12,899 | {
"age": 44,
"workclass": "Local-gov",
"fnlwgt": 185267,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1902,
"hours-per-week": ... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 22,634 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 301031,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 14,472 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 114939,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 38,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 11,797 | {
"age": 32,
"workclass": "Private",
"fnlwgt": 264554,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Tech-support",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 40,892 | {
"age": 46,
"workclass": "Private",
"fnlwgt": 191204,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Never-married",
"occupation": "Exec-managerial",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 26,763 | {
"age": 42,
"workclass": "Self-emp-inc",
"fnlwgt": 130126,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1977,
"hours-per-week... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,353 | {
"age": 37,
"workclass": "Private",
"fnlwgt": 318168,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Machine-op-inspct",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Male",
"capital-gain": 1055,
"capital-loss": 0,
"hours-per-week": 2... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,467 | {
"age": 24,
"workclass": "Private",
"fnlwgt": 62952,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 25,490 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 318915,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 8,276 | {
"age": 48,
"workclass": "Private",
"fnlwgt": 166863,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 9,743 | {
"age": 38,
"workclass": "Private",
"fnlwgt": 35890,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,699 | {
"age": 31,
"workclass": "Private",
"fnlwgt": 369825,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 4101,
"capital-loss": 0,
"hours-per-week": 50,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,799 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 229729,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Transport-moving",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 36,908 | {
"age": 34,
"workclass": "Private",
"fnlwgt": 125279,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,736 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 202878,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Married-civ-spouse",
"occupation": "Farming-fishing",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 2042,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 1,028 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 216479,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,694 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 45713,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Other-relative",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,882 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 132675,
"education": "11th",
"education-num": 7,
"marital-status": "Separated",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-cou... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 4,618 | {
"age": 18,
"workclass": "Local-gov",
"fnlwgt": 28357,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,015 | {
"age": 18,
"workclass": "Private",
"fnlwgt": 148644,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 28,
"native-coun... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 9,857 | {
"age": 57,
"workclass": "Self-emp-not-inc",
"fnlwgt": 200316,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 5... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 48,592 | {
"age": 54,
"workclass": "Private",
"fnlwgt": 161691,
"education": "Masters",
"education-num": 14,
"marital-status": "Divorced",
"occupation": "Prof-specialty",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 2559,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
End of preview.
MEA-Benchmark
A benchmark dataset for evaluating explainability of neural network models across three modalities (tabular, vision, text) with ten question types (Q1–Q10).
Dataset Structure
Each split (train, test) is organized by modality and then by {dataset}_{model}_{q_type}.json:
{split}/
├── tabular/
│ ├── adult_2layernn_q1.json
│ ├── adult_tabnn_q1.json
│ ├── cancer_2layernn_q1.json
│ ├── cancer_tabnn_q1.json
│ └── ...
├── text/
│ ├── imdb_2layernn_q1.json
│ ├── imdb_cnn_q1.json
│ ├── snli_2layernn_q1.json
│ ├── snli_cnn_q1.json
│ └── ...
└── vision/
├── cub_densenet_q1.json
├── cub_resnet_q1.json
├── stl10_densenet_q1.json
├── stl10_resnet_q1.json
└── ...
Fields
| Field | Description |
|---|---|
row_no |
Sample index |
image_path |
Path to input image (vision only) |
modality |
tabular, text, or vision |
dataset |
Dataset name (e.g. adult, cancer, imdb, snli, cub, stl10) |
model |
Model architecture (e.g. 2layernn, tabnn, cnn, resnet, densenet) |
features |
Input features or tokens |
target |
Ground truth label |
predicted |
Model prediction |
example |
Raw input example |
q_type |
Question type (q1–q10) |
q |
The XAI question prompt |
Question Types
- Q1 Most responsible feature
- Q2 Least responsible feature
- Q3 Distinctive feature
- Q4 Contrastive instances
- Q5 Mask prediction
- Q6 Flip prediction
- Q7 Change prediction
- Q8–Q10 Additional reasoning questions
- Downloads last month
- 164