ApplyModels: Title Apply various ML models to your datasets and compare...

In Javad-mun/Beap: Contains the functions used in the Beap lab for physical activity analysis

Description

Title Apply various ML models to your datasets and compare the results

Usage

ApplyModels(working_df, model_names = c("RF", "LDA", "NB", "SVM", "KNN",
  "DT"), split_ratio = 0.66, scale_center = FALSE, cv_folds = 0,
  shrink = 1, save_results_on_disk = TRUE, return_plots = TRUE,
  RF_mtry = 2, min_node_size = 50, cores = 1)

Arguments

working_df	input dataset for classification
model_names	a list of models to be appied on the data
split_ratio	training to test ratio
scale_center	If true, centers and scale the data before modeling
cv_folds	number of folds for cross-validation. Set to zero for not using cross-validation
shrink	the fraction of the data to be used for modeling. If modeling takes to long reduce this.
save_results_on_disk	if set to true results are saved
return_plots	if true returns plots confusion matrix
RF_mtry	minimum number of featuresto be used by the random forest algorithm
min_node_size	minimum number of nodes for the random forest model
cores	number of cores. For parallel computing set it to an integer greater than 1

Value

output a list containing a dataframe containing model names and accuracies and a list of plots and feature importance

Javad-mun/Beap documentation built on July 22, 2020, 3:11 p.m.