Description Usage Arguments Value Author(s) References Examples
A commonly used method with microarrays to select the best genes for class prediction is implemented. This method involves computing the one-way anova for each gene and select the genes with the between classes sum of squares or equivalently the largest F-ratios.
1 | featureSelect(X, y, numFeatures = 10)
|
X |
data matrix |
y |
must be a factor with length equal to the number of rows of X |
numFeatures |
the number of features to be selected - usually larger than the default 10. |
the column indicies corresponding to the columns of X that are selected
A. I. McLeod
tba
1 2 3 4 5 6 | Xy <- churnTrain
y <- Xy[, ncol(Xy)]
Xy <- Xy[, -ncol(Xy)]
X <- as.matrix.data.frame(Xy[,-(1:5)])
(ind <- featureSelect(X, y, numFeatures=5))
colnames(X)[ind]
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.