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### Machine Learning Packages in R

I've been working on a handful of projects lately, and had started to keep track which packages contained the algorithms that I use regularly. Some of them are easy to remember, others aren't. My list has been growing, so I'm posting here to make it easy to keep track of. This is a simple table, but shows the name of the algorithm, tasks it can be used for, and the package that contains it.

I'm including algorithms that I have used or intend to use, so this isn't exhaustive. Let me know if there are any glaring omissions.

Algorithm | Uses | Package |
---|---|---|

Decision Trees | Classification, Regression | rpart |

Gradient Boosted Machine | Classification, Regression | gbm |

Hierarchical Clustering | Clustering | pvclust |

k-Means Clustering | Clustering | Base |

k-Nearest Neighbor | Classification | class |

Lasso | Classification, Regression | glmnet |

Linear Regression | Classification, Regression | Base |

Logistic Regression | Classification | Base |

Model-Based Clustering | Clustering | mclust |

Naïve Bayes | Classification | e1071 or klaR |

Neural Networks | Classification, Regression | nnet |

Random Forest | Classification, Regression | randomForest |

Ridge Regression | Classification, Regression | MASS or ridge |

Spectral Clustering | Clustering | kernlab |

Support Vector Machine | Classification, Regression | e1071 or kernlab |

Linear Discriminant Analysis | Classification | MASS |

| Tagged

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