Conduct Pearson's independence test for every feature against the label. For each feature, the (feature, label) pairs are converted into a contingency matrix for which the Chi-squared statistic is computed. All label and feature values must be categorical.
ml_chisquare_test(x, features, label)A tbl_spark.
The name(s) of the feature columns. This can also be the name
of a single vector column created using ft_vector_assembler().
The name of the label column.
A data frame with one row for each (feature, label) pair with p-values, degrees of freedom, and test statistics.
if (FALSE) { # \dontrun{
sc <- spark_connect(master = "local")
iris_tbl <- sdf_copy_to(sc, iris, name = "iris_tbl", overwrite = TRUE)
features <- c("Petal_Width", "Petal_Length", "Sepal_Length", "Sepal_Width")
ml_chisquare_test(iris_tbl, features = features, label = "Species")
} # }