GuidedSparseKmeans.R2out: GuidedSparseKmeans.R2out

In LingsongMeng/GuidedSparseKmeans: Guided Sparse K-means

Description

Guided Sparse K-means (R-square or pseudo R-square is from the outside)

Usage

GuidedSparseKmeans.R2out(x, R2.per, K, s, lam, nstart = nstart,
  maxiter = 15, silence = F)

Arguments

x	Gene expression matrix, n*p (rows for subjects and columns for genes).
R2.per	R-squared or pseudo R-squared between phenotypic variable and expression value of each gene, a vector.
K	Number of clusters.
s	The boundary of l1n weights, a vector.
lam	The intensity of guidance.
nstart	Specify the number of starting point for K-means.
maxiter	Maximum number of iteration.
silence	Output progress or not.

Details

Guided Sparse K-means integrating clinical dataset with gene expression dataset, R-square or pseudo R-square is from the outside, not calculated in the function.

Value

m lists, m is the length of parameter s. Each list is consisting of

weights	weight for each feature, zero weight means the feature is not selected.
clusters	cluster results.
object	objective value.
bound	a boundary of l1n weights

Author(s)

Lingsong Meng

LingsongMeng/GuidedSparseKmeans documentation built on May 11, 2020, 12:29 a.m.