input.check.FeaLect: Checks the inputs to Fealect() function.
In FeaLect: Scores Features for Feature Selection

Description Usage Arguments Details Value Author(s) References See Also Examples

We should have: F as a matrix, L as a vector, and length of L be equal to number of rows of F. They should have names accordingly.

1	input.check.FeaLect(F_, L_, maximum.features.num, gamma)

`F_`	The feature matrix, each column is a feature.
`L_`	The vector of labels named according to the rows of F.
`maximum.features.num`	Upto this number of features are allowed to contribute to each linear model.
`gamma`	A value in range 0-1 that determines the relative size of sample subsets.

If the input is not appropriate, error or warning message will be produced.

Returns a list of:

`F_`	The feature matrix, each column is a feature.
`L_`	The vector of labels named according to the rows of F.
`maximum.features.num`	Upto this number of features are allowed to contribute to each linear model.

Habil Zare

"Statistical Analysis of Overfitting Features", manuscript in preparation.

FeaLect, train.doctor, doctor.validate, random.subset, compute.balanced,compute.logistic.score, ignore.redundant, input.check.FeaLect

library(FeaLect)
data(mcl_sll)
F <- as.matrix(mcl_sll[ ,-1])	# The Feature matrix
L <- as.numeric(mcl_sll[ ,1])	# The labels
names(L) <- rownames(F)

checked <- input.check.FeaLect(F_=F, L_=L, maximum.features.num=10, gamma=3/4)