feature_importance.classifier: Evaluate Feature Importance
In bbuchsbaum/multivarious: Extensible Data Structures for Multivariate Analysis

feature_importance.classifier

R Documentation

Evaluate Feature Importance

Description

Uses "marginal" or "standalone" approaches:

marginal: remove block and see change in accuracy
standalone: use only that block and measure accuracy

Usage

## S3 method for class 'classifier'
feature_importance(
  x,
  new_data,
  ncomp = NULL,
  blocks = NULL,
  metric = c("cosine", "euclidean", "ejaccard"),
  fun = rank_score,
  normalize_probs = FALSE,
  approach = c("marginal", "standalone"),
  ...
)

Arguments

`x`	classifier
`new_data`	new data
`ncomp`	...
`blocks`	a list of feature indices
`metric`	...
`fun`	a function to compute accuracy (default rank_score)
`normalize_probs`	logical
`approach`	"marginal" or "standalone"
`...`	args to projection