Supervised Learning

Methods to perform a variety of supervised learning tasks.

## Modules | |

Conditional Random Field | |

Constructs a Conditional Random Fields (CRF) model for labeling sequential data. | |

k-Nearest Neighbors | |

Finds \(k\) nearest data points to the given data point and outputs majority vote value of output classes for classification, or average value of target values for regression. | |

Neural Network | |

Solves classification and regression problems with several fully connected layers and non-linear activation functions. | |

Regression Models | |

A collection of methods for modeling conditional expectation of a response variable. | |

Support Vector Machines | |

Solves classification and regression problems by separating data with a hyperplane or other nonlinear decision boundary. | |

Tree Methods | |

A collection of recursive partitioning (tree) methods. | |