Classification: classification—function to perform classification analysis...

In ClassificationEnsembles: Automatically Builds 20 Classification Models

classification—function to perform classification analysis and return results to the user.

Description

classification—function to perform classification analysis and return results to the user.

Usage

Classification(
  data,
  colnum,
  numresamples,
  predict_on_new_data = c("Y", "N"),
  set_seed = c("Y", "N"),
  remove_VIF_above,
  scale_all_numeric_predictors_in_data,
  how_to_handle_strings = c(0("No strings"), 1("Strings as factors")),
  save_all_trained_models = c("Y", "N"),
  save_all_plots,
  use_parallel = c("Y", "N"),
  train_amount,
  test_amount,
  validation_amount
)

Arguments

data	a data set that includes classification data. For example, the Carseats data in the ISLR package
colnum	the number of the column. For example, in the Carseats data this is column 7, ShelveLoc with three values, Good, Medium and Bad
numresamples	the number of times to resample the analysis
predict_on_new_data	asks if the user has new data to be analyzed using the trained models that were just developed
set_seed	Gives the user the option to set a seed
remove_VIF_above	Removes columns with Variance Inflation Factors above the level chosen by the user
scale_all_numeric_predictors_in_data	Scales all numeric predictors in the original data
how_to_handle_strings	Converts strings to factor levels
save_all_trained_models	Gives the user the option to save all trained models in the Environment
save_all_plots	Saves all plots in the user's chosen format
use_parallel	"Y" or "N" for parallel processing
train_amount	set the amount for the training data
test_amount	set the amount for the testing data
validation_amount	Set the amount for the validation data

Value

a full analysis, including data visualizations, statistical summaries, and a full report on the results of 35 models on the data

ClassificationEnsembles documentation built on Aug. 8, 2025, 6:40 p.m.