R: Importance of features in a model.

gbt.importance {agtboost} | R Documentation

## Importance of features in a model.

### Description

`gbt.importance` creates a `data.frame` of feature importance in a model

### Usage

    gbt.importance(feature_names, object)

### Arguments

`feature_names` | character vector of feature names
`object` | object or pointer to object of class `ENSEMBLE`

### Details

Sums up "expected reduction" in generalization loss (scaled using `learning_rate`) at each node for each tree in the model, and attributes it to the feature the node is split on. Returns result in terms of percents.

### Value

`data.frame` with percentwise reduction in loss of total attributed to each feature.

### Examples

    ## Load data
    data(caravan.train, package = "agtboost")
    train <- caravan.train
    mod <- gbt.train(train$y, train$x, loss_function = "logloss", verbose=10)
    feature_names <- colnames(train$x)
    imp <- gbt.importance(feature_names, mod)
    imp

[Package agtboost version 0.9.3 Index]