Data
Intersectional-Bias-Assessment-(Training-Data)

Intersectional-Bias-Assessment-(Training-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 train a classifier to predict a diagnosis (of schizophrenia or depression). 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
Anhedonianumeric10000 unique values
0 missing
Dep_Moodnumeric10000 unique values
0 missing
Sleepnumeric10000 unique values
0 missing
Tirednumeric10000 unique values
0 missing
Appetitenumeric10000 unique values
0 missing
Ruminationnumeric10000 unique values
0 missing
Concentrationnumeric10000 unique values
0 missing
Psychomotornumeric10000 unique values
0 missing
Delusionnumeric10000 unique values
0 missing
Suspiciousnumeric10000 unique values
0 missing
Withdrawalnumeric10000 unique values
0 missing
Passivenumeric10000 unique values
0 missing
Tensionnumeric9999 unique values
0 missing
Unusual_Thoughtnumeric10000 unique values
0 missing
Show all 19 features

19 properties

NumberOfInstances
10000
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.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
0.5
Average class difference between consecutive instances.
Dimensionality
0
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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