Description Usage Arguments Value Author(s) Examples
View source: R/sigFeatureSelection.R
This function extracting informative features with feature selection algorithms including the student's t-test and chi-square test feature selection algorithms.
1 | sigFeatureSelection(featureMatrix, positives, negatives, binary = FALSE, level = 0.05)
|
featureMatrix |
A numeric matrix of features where rows represent genes, cols represent features |
positives |
A character vector of positive samples |
negatives |
A character vector of negative samples |
binary |
A logical value, where TRUE represents the features are binary with 0 and 1, the default is FALSE |
level |
A numeric value recording the significant level, the default is 0.05 |
A numeric feature matrix with only significant features were contained
Jingjing Zhai, Chuang Ma
1 2 3 4 5 6 7 8 9 | ## Not run:
positives <- c("AT1G01060", "AT1G09530", "AT1G09570", "AT1G12610")
sifFeatureMat <- sigFeatureSelection(featureMatrix = featureMat,
positives = positives,
negatives = negatives)
## featureMat can be calculated by function FeatureExtract
## negatives can be calculated by function selectNegSamples
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.