chty: chty

In SpNMF: Supervised NMF

Description

chty is used to get number of types for the data.

Usage

chty(data,y,k,maxr)

Arguments

data	an optional n by p count data matrix. The p columns of the matrix are different variables and the n rows are samples. Each column should contain at lest one none zero entry. When n = 1, it is a row vector.
y	a binary variable contains classification information of the data. Usually one group is labelled as "0" and the other as "1".
k	a value gives the number of folds used in cross validation when choosing number of types.
maxr	a number gives the upper bound of the number of types.

Value

r1	the suggested number of types for class labeled as 1.
r2	the suggested number of types for class labeled as 0.

Author(s)

Yun Cai, Hong Gu and Toby Kenney

References

Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization

Examples

##we use the simulated data spdata here
##the spdata is simulated from feature matrix combined by 2
#3types features from one group and 3 types from the other.
##choose number of types using our function
##2-folds cross validation is used here
##the upper bound of number of types for both classes is 2
##remove all zero variables from the data
spdata.rm=spdata[c(1:4,41:44),colSums(spdata)!=0]
y=c(rep(1,4),rep(0,4))
types=chty(spdata.rm,y,2,2)
#number of types for class labeled as 1
nmb1 = types$r1
#number of types for class labeled as 0
nmb2 = types$r2

SpNMF documentation built on May 2, 2019, 3:33 p.m.