/home/jenkins-mlpack/mlpack.org/_src/mlpack-3.2.1/doc/tutorials/det/det.txt File Reference

Tutorial for how to perform density estimation with Density Estimation Trees (DET). More...

## Functions | |

f f | $V (t)\f$ is the volume of the node \f $t\f$ and \f$\tilde |

see subsection cli_alt_reg_tut Alternate DET regularization The usual regularized error f $R_ | alpha (t)\f$ of a node \f $t\f$ is given by |

## Variables | |

f is the set of leaves in the subtree rooted at f $t f For the purposes of density | estimation |

this option is not available in DET right | now |

f is the set of leaves in the subtree rooted at f $t f For the purposes of density there is a different form of | regularization |

f is the set of leaves in the subtree rooted at f $t f For the purposes of density there is a different form of we penalize the sum of the inverse of the volumes of the leaves With this very small volume nodes are discouraged unless the data actually warrants it | Thus |

Tutorial for how to perform density estimation with Density Estimation Trees (DET).

Definition in file det.txt.

see subsection cli_alt_reg_tut Alternate DET regularization The usual regularized error f $R_ alpha | ( | t | ) |

f is the set of leaves in the subtree rooted at f $t f For the purposes of density estimation |

f is the set of leaves in the subtree rooted at f $t f For the purposes of density there is a different form of we penalize the sum of the inverse of the volumes of the leaves With this regularization |

f is the set of leaves in the subtree rooted at f $t f For the purposes of density there is a different form of we penalize the sum of the inverse of the volumes of the leaves With this very small volume nodes are discouraged unless the data actually warrants it Thus |