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Intersectional-Bias-Assessment-(Training-Data)

Intersectional-Bias-Assessment-(Training-Data)

active ARFF CC-4Y Visibility: public Uploaded 19-09-2022 by Robertson
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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
Appetitenumeric10000 unique values
0 missing
Unusual_Thoughtnumeric10000 unique values
0 missing
Tensionnumeric9999 unique values
0 missing
Passivenumeric10000 unique values
0 missing
Withdrawalnumeric10000 unique values
0 missing
Suspiciousnumeric10000 unique values
0 missing
Delusionnumeric10000 unique values
0 missing
Psychomotornumeric10000 unique values
0 missing
Concentrationnumeric10000 unique values
0 missing
Ruminationnumeric10000 unique values
0 missing
Tirednumeric10000 unique values
0 missing
Sleepnumeric10000 unique values
0 missing
Dep_Moodnumeric10000 unique values
0 missing
Anhedonianumeric10000 unique values
0 missing
Delaystring2 unique values
0 missing
Housingstring2 unique values
0 missing
Racestring4 unique values
0 missing
Sexstring2 unique values
0 missing

19 properties

10000
Number of instances (rows) of the dataset.
19
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
15
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of nominal attributes.
0.5
Average class difference between consecutive instances.
78.95
Percentage of numeric attributes.
0
Percentage of missing values.
0
Percentage of instances having missing values.
0
Percentage of binary attributes.
0
Number of binary attributes.
Number of instances belonging to the least frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the most frequent class.
0
Number of attributes divided by the number of instances.

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