estimateFeatureImportance: Estimates the importance of each feature in the model object

In predomics/predomicspkg: Interpretable Prediction in Omics Data

Estimates the importance of each feature in the model object

Description

Estimates the importance of each feature in the model object

Usage

estimateFeatureImportance(
  mod,
  X,
  y,
  clf,
  attribute = "unpenalized_fit_",
  plot.importance = FALSE
)

Arguments

mod:	a model object
X:	the data matrix with variables in the rows and observations in the columns
y:	the response vector
clf:	the classifier parameter object
attribute:	which attribute should be used to compute the importance (default:unpenalized_fit_)
plot.importance:	should the function plot the improtance of the features (default:FALSE)

Value

a model object with the importance of each feature computed. Negative importance of a feature means that the feature is not beneficial.

predomics/predomicspkg documentation built on Dec. 11, 2024, 11:06 a.m.