nsel

an object of <code><a rd-options="" href="/link/mhingebst?package=bst&version=0.3-13" data-mini-rdoc="bst::mhingebst">mhingebst</a></code>, <code><a rd-options="" href="/link/mbst?package=bst&version=0.3-13" data-mini-rdoc="bst::mbst">mbst</a></code>, or <code><a rd-options="" href="/link/rmbst?package=bst&version=0.3-13" data-mini-rdoc="bst::rmbst">rmbst</a></code>

object

mstop

 Find Number of Variables In Multi-class Boosting Iterations

Functional gradient descent algorithm for a variety of convex and nonconvex loss functions, for both classical and robust regression and classification problems. HingeBoost is implemented for binary and multi-class classification, with unequal misclassification costs for binary case. The algorithm can fit linear and nonlinear classifiers.

nsel: Find Number of Variables In Multi-class Boosting Iterations

Description

Usage

Arguments

Value