When predicting from a model, it is often important for the new_data to have the same classes as the original data used to fit the model. get_data_classes() extracts the classes from the original training data.

get_data_classes(data)

Arguments

data

A data frame or matrix.

Value

A named list. The names are the column names of data and the values are character vectors containing the class of that column.

Examples

get_data_classes(iris)
#> $Sepal.Length #> [1] "numeric" #> #> $Sepal.Width #> [1] "numeric" #> #> $Petal.Length #> [1] "numeric" #> #> $Petal.Width #> [1] "numeric" #> #> $Species #> [1] "factor" #>
get_data_classes(as.matrix(mtcars))
#> $mpg #> [1] "numeric" #> #> $cyl #> [1] "numeric" #> #> $disp #> [1] "numeric" #> #> $hp #> [1] "numeric" #> #> $drat #> [1] "numeric" #> #> $wt #> [1] "numeric" #> #> $qsec #> [1] "numeric" #> #> $vs #> [1] "numeric" #> #> $am #> [1] "numeric" #> #> $gear #> [1] "numeric" #> #> $carb #> [1] "numeric" #>
# Unlike .MFclass(), the full class # vector is returned data <- data.frame(col = ordered(c("a", "b"))) .MFclass(data$col)
#> [1] "ordered"
get_data_classes(data)
#> $col #> [1] "ordered" "factor" #>