fit_rf: Fit Random Forest

In antonvsdata/amp: Smoothing Metabolomics Analyses

Description

Fits a random forest, where given response column in pheno data is predicted using the features. Can be used both for classification and regression. For more information, see the documentation of randomForest::randomForest. After fitting the random forest, use rf_importance as a shortcut for getting the feature importance in random forest prediction.

Usage

fit_rf(object, response, all_features = FALSE, importance = TRUE, ...)

Arguments

object	a MetaboSet object
response	character, column name of phenoData giving response
all_features	should all features be included in the model? if FALSE, flagged features are left out
importance	Should importance of features be assessed?
...	other parameters passed to randomForest::randomForest

Value

An object of class randomForest

See Also

randomForest, rf_importance

Examples

rf <- fit_rf(example_set, response = "Group")
rf
importance_rf(rf)

antonvsdata/amp documentation built on Jan. 8, 2020, 3:15 a.m.