Dimensionality Reduction

Methods for reducing the number of variables in a dataset to obtain a set of principle variables.

## Modules | |

Principal Component Analysis | |

Produces a model that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables called principal components. | |

Principal Component Projection | |

Projects a higher dimensional data point to a lower dimensional subspace spanned by principal components learned through the PCA training procedure. | |