SYNOPSIS

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"

Detailed Description

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

Author:

Parikshit Ram

Definition in file det.txt.

Function Documentation

f f $V (t)

Definition at line 374 of file det.txt.

see subsection cli_alt_reg_tut Alternate DET \fBregularization\fP The usual regularized error f $R_ alpha (t)

Definition at line 367 of file det.txt.

Variable Documentation

f is the \fBset\fP of leaves in the subtree rooted at f $t f For the purposes of density estimation

Definition at line 377 of file det.txt.

this option is not available in DET right now

Definition at line 364 of file det.txt.

f is the \fBset\fP 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

Definition at line 377 of file det.txt.

f is the \fBset\fP 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

Definition at line 377 of file det.txt.

Author

Generated automatically by Doxygen for MLPACK from the source code.