R: Calculate a simple measure of 'importance' for each feature.

variable_importance {grf} | R Documentation

## Calculate a simple measure of 'importance' for each feature.

### Description

A simple weighted sum of how many times feature i was split on at each depth in the forest.

### Usage

    variable_importance(forest, decay.exponent = 2, max.depth = 4)

### Arguments

`forest` | The trained forest.
`decay.exponent` | A tuning parameter that controls the importance of split depth.
`max.depth` | Maximum depth of splits to consider.

### Value

A list specifying an 'importance value' for each feature.

### Examples

    ## Not run:
    # Train a quantile forest.
    n <- 50
    p <- 10
    X <- matrix(rnorm(n * p), n, p)
    Y <- X[, 1] * rnorm(n)
    q.forest <- quantile_forest(X, Y, quantiles = c(0.1, 0.5, 0.9))

    # Calculate the 'importance' of each feature.
    variable_importance(q.forest)

    ## End(Not run)

[Package grf version 1.0.0 Index]