make.predictions {SIAMCAT} | R Documentation

## Make predictions on a test set

### Description

This function takes a siamcat-class-object containing a model trained by train.model and performs predictions on a given test-set.

### Usage

    make.predictions(siamcat, siamcat.holdout = NULL,
        normalize.holdout = TRUE, verbose = 1)

### Arguments

`siamcat` | object of class siamcat-class
`siamcat.holdout` | optional, object of class siamcat-class on which to make predictions, defaults to `NULL`
`normalize.holdout` | boolean, should the holdout features be normalized with a frozen normalization (see normalize.features) using the normalization parameters in `siamcat`?, defaults to `TRUE`
`verbose` | integer, control output: `0` for no output at all, `1` for only information about progress and success, `2` for normal level of information and `3` for full debug information, defaults to `1`

### Details

This functions uses the model in the `model_list`-slot of the `siamcat` object to make predictions on a given test set. The test set can either consist of the test instances in the cross- validation, saved in the `data_split`-slot of the same `siamcat` object, or a completely external feature set, given in the form of another `siamcat` object (`siamcat.holdout`).

### Value

object of class siamcat-class with the slot `pred_matrix` filled

### Examples

    data(siamcat_example)

    # Simple example
    siamcat.pred <- make.predictions(siamcat_example)

    # Predictions on a holdout-set
    pred.mat <- make.predictions(siamcat.trained, siamcat.holdout,
        normalize.holdout=TRUE)

[Package SIAMCAT version 1.10.0 Index]