Definition
Calibration describs the agreement between observed outcomes and predictions. The most common definition of calibration is that if we observe p% risk among patients with a predicted risk of p%.
Original paper
Varma, S., Simon, R. Bias in error estimation when using cross-validation for model selection. BMC Bioinformatics 7, 91 (2006).
Background
Cross-validation (CV) is an effective method for estimating the prediction error of a classifier.
The goal of this article is to gathering thoughts about variable selection.
Consensus features nested cross-validation
Bioinformatics, Volume 36, Issue 10, 15 May 2020, Pages 3093–3098
Background
Feature selection
There are multiple ways to use feature selection with classification to address the bias-variance tradeoff.