Data
Intersectional-Bias-Assessment-(Testing-Data)

Intersectional-Bias-Assessment-(Testing-Data)

active ARFF CC-4Y Visibility: public Uploaded 19-09-2022 by Manojit Nandi
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This synthetic dataset contains demographic and clinical data used to test the performance of a trained classifier in predicting a diagnosis (of schizophrenia or depression), and assess performance for intersectional bias. This dataset is used in the tutorial 'An Intersectional Approach to Model Construction and Evaluation in Mental Health Care' presented at ACM FAccT 2022.

19 features

Diagnosis (target)numeric2 unique values
0 missing
Sexstring2 unique values
0 missing
Racestring4 unique values
0 missing
Housingstring2 unique values
0 missing
Delaystring2 unique values
0 missing
Anhedonianumeric1000 unique values
0 missing
Dep_Moodnumeric1000 unique values
0 missing
Sleepnumeric1000 unique values
0 missing
Tirednumeric1000 unique values
0 missing
Appetitenumeric1000 unique values
0 missing
Ruminationnumeric1000 unique values
0 missing
Concentrationnumeric1000 unique values
0 missing
Psychomotornumeric1000 unique values
0 missing
Delusionnumeric1000 unique values
0 missing
Suspiciousnumeric1000 unique values
0 missing
Withdrawalnumeric1000 unique values
0 missing
Passivenumeric1000 unique values
0 missing
Tensionnumeric1000 unique values
0 missing
Unusual_Thoughtnumeric1000 unique values
0 missing
Show all 19 features

19 properties

NumberOfInstances
1000
Number of instances (rows) of the dataset.
NumberOfFeatures
19
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
15
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
0.53
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Dimensionality
0.02
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
78.95
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
Show all 19 properties

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