TangledFeatures: The main TangledFeatures function

In TangledFeatures: Feature Selection in Highly Correlated Spaces

The main TangledFeatures function

Description

The main TangledFeatures function

Usage

TangledFeatures(
  Data,
  Y_var,
  Focus_variables = list(),
  corr_cutoff = 0.7,
  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')

TangledFeatures documentation built on Feb. 16, 2023, 9:48 p.m.