Regression models predict a value Y given a set of X variables.
In the regression model $Y \sim X$, we measure the effect of $X$ on $Y$, i.e., we measure the association between changes in values of $X$ and changes in values of $Y$.
Analyzing a regression model is a method used to solve a regression problem.

Regression Models

- Regression Models
- Decision Tree Models
- Random Forest Models
- Support Vector Machine
- Naive Bayes
- K Means
- KNN

University of Michigan - Ann Arbor

Johns Hopkins University

Methods of supervised statistical learning

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, pp. 3-7). New York: springer.

An Introduction to Statistical Learning with Applications in R

Classical SL Methods (examples)

- GAM
- Boosting
- Support vector machines

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