The main TangledFeatures function

Usage

TangledFeatures(
  Data,
  Y_var,
  Focus_variables = list(),
  corr_cutoff = 0.85,
  RF_coverage = 0.95,
  plot = FALSE,
  fast_calculation = FALSE,
  cor1 = "pearson",
  cor2 = "polychoric",
  cor3 = "spearman"
)

Arguments

Data: The imported Data Frame
Y_var: The dependent variable
Focus_variables: The list of variables that you wish to give a certain bias to in the correlation matrix
corr_cutoff: The correlation cutoff variable. Defaults to 0.8
RF_coverage: The Random Forest coverage of explainable. Defaults to 95 percent
plot: Return if plotting is to be done. Binary True or False
fast_calculation: Returns variable list without many Random Forest iterations by simply picking a variable from a correlated group
cor1: The correlation metric between two continuous features. Defaults to pearson correlation
cor2: The correlation metric between one categorical feature and one continuous feature. Defaults to bi serial correlation correlation
cor3: The correlation metric between two categorical features. Defaults to Cramer's V.

Value

Returns a list of variables that are ready for future modelling, along with other metrics

Examples

TangledFeatures(Data = TangledFeatures::Advertisement, Y_var = 'Sales')
#> Warning: length(LHS)==0; no columns to delete or assign RHS to.
#> $Final_Variables
#> [1] "tv"    "radio"
#> 
#> $Variable_groups
#> NULL
#> 
#> $Correlation_heatmap
#> NULL
#> 
#> $Graph_plot
#> NULL
#>