roc_scores: ROC scores

Description Usage Arguments Details Examples

Description

This function provides a way to identify the worst predictions when measuring Area Under the ROC curve. Simply put, the worst predictions are the ones with very low or high relative prediction scores (usually probabilities) which relate to the positive and negative samples respectively.

Usage

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roc_scores(preds, actuals)

Arguments

preds

vector of predictions (need not be in range [0-1] - only order matters)

actuals

vector of actuals - either logical or vector of 1s and 0s

Details

How it works

Examples

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roc_scores(c(1,2,3,4), actuals=c(1,1,0,0))
roc_scores(c(0.1, 0.2, 0.3, 0.4), actuals=c(TRUE, FALSE, TRUE, FALSE))

mltools documentation built on May 2, 2019, 5:22 a.m.