x.scaleL

a numeric object with n rows and p columns.

the index set to define the means and variances.

a flag to indicate whether <code>x</code> should be converted to a &#8216;matrix&#8217; form.

sanity

this flag bypasses the scaling but does coerce <code>x</code> to a &#8216;matrix&#8217;.

sanity.only

This method centers and scales the columns of a numeric matrix using the means and columns derived from a subset of
	its indices.

classes

models

methods

Implements several safe graph-based semi-supervised learning algorithms. The first algorithm is the Semi-Supervised Semi-Parametric Model (S4PM) and the fast Anchor Graph version of this approach. For additional technical details, refer to Culp and Ryan (2013) <http://jmlr.org/papers/v14/culp13a.html>, Ryan and Culp (2015) <http://www.jmlr.org/papers/v16/ryan15a.html> and the package vignette. The underlying fitting routines are executed in C++. All tuning parameter estimation is optimized using K-fold Cross-Validation.

x.scaleL: Scale a data set in accordance to a labeled index set

Description

Usage

Arguments