1 Introduction
2 Visualizations
3 Pre-Processing
4 Data Splitting
5 Model Training and Tuning
6 Available Models
7 train Models By Tag
8 Models Clustered by Tag Similarity
9 Parallel Processing
10 Random Hyperparameter Search
11 Subsampling For Class Imbalances
12 Using Recipes with train
13 Using Your Own Model in train
14 Adaptive Resampling
15 Variable Importance
16 Miscellaneous Model Functions
17 Measuring Performance
18 Feature Selection Overview
19 Feature Selection using Univariate Filters
20 Recursive Feature Elimination
21 Feature Selection using Genetic Algorithms
22 Feature Selection using Simulated Annealing
23 Data Sets
24 Session Information

The `caret` Package

6 Available Models

The models below are available in train. The code behind these protocols can be obtained using the function getModelInfo or by going to the github repository.