predict.regression_model_fit: Predict continuous values for a new dataset using a...

In bbuchsbaum/rMVPA: Multivoxel Pattern Analysis in R

Predict continuous values for a new dataset using a regression model

Description

This function predicts continuous values for new data using a fitted regression model.

Usage

## S3 method for class 'regression_model_fit'
predict(object, newdata, sub_indices = NULL, ...)

Arguments

object	A fitted model object of class regression_model_fit.
newdata	New data to predict on, either as a matrix or a NeuroVec or NeuroSurfaceVector object.
sub_indices	A vector of indices used to subset rows of 'newdata' (optional).
...	Additional arguments to be passed to the underlying prediction function.

Value

A list containing predicted continuous values with class attributes "regression_prediction", "prediction", and "list".

Examples

# Assuming `fitted_model` is a fitted model object of class `regression_model_fit`
new_data <- iris_dataset$test_data
predictions <- predict(fitted_model, new_data)

bbuchsbaum/rMVPA documentation built on April 28, 2024, 6:30 a.m.