build_hist_binning function

build_hist_binning

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

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

Returns

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

Details

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