dsld (version 0.2.2)

dsldTakeALookAround: dsldTakeALookAround

Description

Evaluate feature sets for predicting Y while considering the Fairness-Utility Tradeoff.

Usage

dsldTakeALookAround(data, yName, sName, maxFeatureSetSize = (ncol(data) - 2), 
    holdout = floor(min(1000,0.1*nrow(data))))

Value

Data frame whose first column consists of the variable names, followed by columns 'a', 'b' and 'c' as described in 'details'.

Arguments

data

Data frame.

yName

Name of the response variable column.

sName

Name of the sensitive attribute column.

maxFeatureSetSize

Maximum number of combinations of features to be included in the data frame.

holdout

If not NULL, form a holdout set of the specified size. After fitting to the remaining data, evaluate accuracy on the test set.

Author

N. Matloff, A. Ashok, S. Martha, A. Mittal

Details

This function provides a tool for exploring feature combinations to use in predicting an outcome Y from features X and a sensitive variable S.

The features in X will first be considered singly, then doubly and so on, up though feature combination size maxFeatureSetSize. Y is prediction from X either a linear model (numeric Y) or logit (dichotomous Y).

The accuracy (based on qeML holdout) will be computed for each of these cases: (a) Y predicted from the given feature combination C, (b) Y predicted from the given feature combination C plus S, and (c) S predicted from C. The difference between columns 'a' and 'b' shows the sacrifice in utility stemming from not using S in our prediction of Y. (Due to sampling variation, it is possible for column 'b' to be larger than 'a'.) The value in column 'c' shows fairness, the smaller the fairer.

Examples

# \donttest{
# investigate predictive accuracy for a continuous Y,
# 'wageinc', using the default arguments for maxFeatureSetSize = 4
data(svcensus)
dsldTakeALookAround(svcensus, 'wageinc', 'gender', 4)

# investigate the predictive accuracy for a categorical Y, 
# 'educ', using the default arguments for maxFeatureSetSize = 4
dsldTakeALookAround(svcensus, 'educ', 'gender')# }