Preprocess a dataframe of covariate values, converting categorical variables to integers and one-hot encoding if need be. Returns a list including a matrix of preprocessed covariate values and associated tracking.

Preprocess a dataframe of covariate values, converting categorical variables to integers and one-hot encoding if need be. Returns a list including a matrix of preprocessed covariate values and associated tracking.

Usage

createForestCovariatesFromMetadata(input_data, metadata)

Arguments

input_data

Dataframe or matrix of covariates. Users may pre-process any categorical variables as factors but it is not necessary.

metadata

List containing information on variables, including train set categories for categorical variables

Value

Preprocessed data with categorical variables appropriately preprocessed

Examples

cov_df <- data.frame(x1 = 1:5, x2 = 5:1, x3 = 6:10)
metadata <- list(num_ordered_cat_vars = 0, num_unordered_cat_vars = 0, 
                 num_numeric_vars = 3, numeric_vars = c("x1", "x2", "x3"))
X_preprocessed <- createForestCovariatesFromMetadata(cov_df, metadata)