Nothing
new_ml_model_linear_svc <- function(pipeline_model, formula, dataset, label_col,
features_col, predicted_label_col) {
m <- new_ml_model_classification(
pipeline_model, formula,
dataset = dataset,
label_col = label_col, features_col = features_col,
predicted_label_col = predicted_label_col,
class = "ml_model_linear_svc"
)
model <- m$model
jobj <- spark_jobj(model)
coefficients <- model$coefficients
names(coefficients) <- m$feature_names
m$coefficients <- if (ml_param(model, "fit_intercept")) {
rlang::set_names(
c(invoke(jobj, "intercept"), model$coefficients),
c("(Intercept)", m$feature_names)
)
}
m
}
#' @export
print.ml_model_linear_svc <- function(x, ...) {
cat("Formula: ", x$formula, "\n\n", sep = "")
cat("Coefficients:", sep = "\n")
print(x$coefficients)
}
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