example

<p>list object containing 1) the simulated classifiers for two classes. Distributions are simulated from Gaussian distributions with
Normal(mean=1.5, sd=0) for class 1 and Normal(mean=0, sd=0) for class 0 instances. Each class consists of 100 instances.
and 2) A test set of 100 instances</p>

datasets

Transforms your uncalibrated Machine Learning scores to well-calibrated prediction estimates that can be interpreted as probability estimates. The implemented BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015, ISBN:0-262-51129-0). Please cite this paper: Schwarz J and Heider D, Bioinformatics 2019, 35(14):2458-2465.

Dominik Heider

CalibratR

Mapping ML Scores to Calibrated Predictions

example function

<p><code>predicted</code>=vector of 200 simulated classifier values; <code>actual</code>=their respective true class labels (0/1)</p>

example: example

Description

Usage

Arguments

Format