build_hist_binning: build_hist_binning

In CalibratR: Mapping ML Scores to Calibrated Predictions

Description

calculate estimated probability per bin, input predicted and real score as numeric vector; builds a histogram binning model which can be used to calibrate uncalibrated predictions using the predict_histogramm_binning method

Usage

build_hist_binning(actual, predicted, bins = NULL)

Arguments

actual	vector of observed class labels (0/1)
predicted	vector of uncalibrated predictions
bins	number of bins that should be used to build the binning model, Default: decide_on_break estimates optimal number of bins

Details

if trainings set is smaller then threshold (15 bins*5 elements=75), number of bins is decreased

Value

returns the trained histogram model that can be used to calibrate a test set using the predict_hist_binning method

CalibratR documentation built on Aug. 19, 2019, 5:04 p.m.