Step | Description |
---|---|
step_knnimputation | Impute missing values using the k-nearest neighbor algorithm |
step_BoxCox | Transform numeric data using simple Box-Cox transformation |
step_other | Pool less frequent categories into an "other" category for categorical variables |
step_zv | Remove variables that have a single value |
step_nzv | Remove variables having the frequency ratio of their first and second frequent values above 95/5 and the number of unique values over the total number of samples below 10% |
step_normalize | Normalize numeric variables to have zero mean and one unit of variance (standard deviation = 1) |
step_dummy | Covert each level of categorical variables into a numeric binary term |
step_corr | Remove variables that are highly correlated with other variables (absolute correlation values > = 0.9) |