PCAyd-class

The function PCAy returns object of class PCAyd.

classes

PCAyd

It's a Super K-Nearest Neighbor(SKNN) classification method with using kernel density to describe weight of the distance between a training observation and the testing sample. Comparison of performance between SKNN and KNN shows that SKNN is significantly superior to KNN.

Yi Ya

SKNN

A Super K-Nearest Neighbor (SKNN) Classification Algorithm

Yarong Yang

Nader Ebrahimi

Yoram Rubin

Jacob Zhang

PCAyd function

new("PCAyd",Var=new("numeric"),PC=new("matrix"),Scores=new("matrix"),IScores=new("numeric"))

Objects from the Class

<dl>
 <dt><code>Var</code>:</dt>
<dd>An numeric vector giving the variance of each PC.</dd> <dt><code>PC</code>:</dt>
<dd>A numeric matrix about the coefficients of each PC.</dd> <dt><code>Scores</code>:</dt>
<dd>A numeric matrix showing the loading coefficiens of each PC.</dd> <dt><code>IScores</code>:</dt>
<dd>A numeric vector with each element being the rowsum of Scores.</dd> 
</dl>

Slots

Author

Class to contain the results from revised PCA analysis. — PCAyd

<dl>
 <dt><code>Var</code>:</dt>
<dd>An numeric vector giving the variance of each PC.</dd>

 <dt><code>PC</code>:</dt>
<dd>A numeric matrix about the coefficients of each PC.</dd>

 <dt><code>Scores</code>:</dt>
<dd>A numeric matrix showing the loading coefficiens of each PC.</dd>

 <dt><code>IScores</code>:</dt>
<dd>A numeric vector with each element being the rowsum of Scores.</dd>

 
</dl>

PCAyd: Class to contain the results from revised PCA analysis.

Description

Arguments

Objects from the Class

Slots

Author

References

Examples