L2PCA_approx

l2pcaapprox

Provides an approximation of traditional PCA described by Park and Klabjan (2016) as a subroutine for awl1pca.

Implementations of several methods for principal component analysis
using the L1 norm. The package depends on COIN-OR Clp version >=
1.17.4. The methods implemented are
PCA-L1 (Kwak 2008) <DOI:10.1109/TPAMI.2008.114>,
L1-PCA (Ke and Kanade 2003, 2005) <DOI:10.1109/CVPR.2005.309>,
L1-PCA* (Brooks, Dula, and Boone 2013) <DOI:10.1016/j.csda.2012.11.007>,
L1-PCAhp (Visentin, Prestwich and Armagan 2016)
<DOI:10.1007/978-3-319-46227-1_37>,
wPCA (Park and Klabjan 2016) <DOI: 10.1109/ICDM.2016.0054>,
awPCA (Park and Klabjan 2016) <DOI: 10.1109/ICDM.2016.0054>,
PCA-Lp (Kwak 2014) <DOI:10.1109/TCYB.2013.2262936>, and
SharpEl1-PCA (Brooks and Dula, submitted).

Paul Brooks

pcaL1

L1-Norm PCA Methods

L2PCA_approx function

<dl> <dt>ev.prev</dt>
<dd>matrix of principal component loadings from a previous iteration of awl1pca</dd> <dt>pc.prev</dt>
<dd>vector of eigenvalues from previous iteration of awl1pca</dd> <dt>projDim</dt>
<dd>number of dimensions to project data into, must be an integer</dd> <dt>X.diff</dt>
<dd>The difference between the current weighted matrix estimate and the estimate from the previous iteration</dd></dl>

Arguments

L2PCA_approx — L2PCA_approx

<dl>

 <dt>ev.prev</dt>
<dd>matrix of principal component loadings from a previous iteration of awl1pca</dd>

 <dt>pc.prev</dt>
<dd>vector of eigenvalues from previous iteration of awl1pca</dd>

 <dt>projDim</dt>
<dd>number of dimensions to project data into, must be an integer</dd>

 <dt>X.diff</dt>
<dd>The difference between the current weighted matrix estimate and the estimate from the previous iteration</dd>

</dl>

L2PCA_approx: L2PCA_approx

Description

Usage

Value

Arguments

Details

References

See Also