Make predictions on a test set — make.predictions • SIAMCAT

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

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`

Value

object of class siamcat-class with the slot pred_matrix filled

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).

Examples

data(siamcat_example)

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

# Predictions on a holdout-set
pred.mat <- make.predictions(siamcat.trained, siamcat.holdout,
    normalize.holdout=TRUE)
#> Error in make.predictions(siamcat.trained, siamcat.holdout, normalize.holdout = TRUE): object 'siamcat.holdout' not found