feature_weights {SIAMCAT} | R Documentation

## Retrieve the matrix of feature weights from a SIAMCAT object

### Description

Function to extract the feature weights from a SIAMCAT object

### Usage

    feature_weights(siamcat, verbose=1)

    ## S4 method for signature 'siamcat'
    feature_weights(siamcat, verbose = 1)

### Arguments

`siamcat` | (Required). A siamcat-class object that contains trained models
`verbose` | integer, if the slot is empty, should a message be printed? values can be either `0` (no output) or `1` (print message)

### Details

The function extracts the weight matrix from all trained models (see weight_matrix) and computes several metrics on the feature weights:

- `mean.weight` - mean weight across trained models

- `median.weight` - median weight across trained models

- `sd.weight` - standard deviation of the weight across trained models

- `mean.rel.weight` - mean relative weight across trained models (each model is normalized by the absolute of all weights)

- `median.rel.weight` - median relative weight across trained models

- `sd.rel.weight` - standard deviation of the relative weight across trained models

- `percentage` - percentage of models in which this feature was selected (i.e. non-zero)

### Value

A dataframe containing mean/median feature weight and additional info or `NULL`

### Examples

    data(siamcat_example)
    temp <- feature_weights(siamcat_example)
    head(temp)

[Package SIAMCAT version 1.6.0 Index]