The Akaike Information Criterion for model selection
The Akaike Information Criterion (AIC) is another tool to compare prediction models. AIC combines model accuracy and parsimony in a single metric and can be used to evaluate data …
Category: Regression Model Validation
The Concordance Correlation Coefficient
Regression, Regression metrics, Regression Model Validation
01/09/2021
The Concordance Correlation Coefficient (CCC) can be useful to quantify the quality of a linear regression model. In this tutorial we explain the CCC and describe its relation with …
Bias-Variance trade-off in PLS regression
Bias-Variance trade-off refers to the optimal choice of parameters in a model in order to avoid both overfitting and underfitting. Let's look at a worked example using PLS regression.
K-fold and Montecarlo cross-validation vs Bootstrap: a primer
Cross-validation is a standard procedure to quantify the robustness of a regression model. Compare K-Fold, Montecarlo and Bootstrap methods and learn some neat trick in the process.
