pca

fun pca(data: DataFrame, cor: Boolean = false, vararg columns: String): PCA(source)

Principal component analysis on a data frame.

the PCA model.

data

training data.

cor

true to use correlation matrix instead of covariance matrix.

columns

the column names to use. If empty, all columns are used.

fun pca(data: Array<DoubleArray>, cor: Boolean = false, vararg columns: String): PCA(source)

Principal component analysis on a raw matrix.

the PCA model.

data

training data of which each row is a sample.

cor

true to use correlation matrix instead of covariance matrix.

columns

optional column names for projected data frame.