predict_functions: Examples of predict_fn functions
In cvms: Cross-Validation for Model Selection

predict_functions

R Documentation

Examples of predict_fn functions

\Sexpr[results=rd, stage=render]{lifecycle::badge("experimental")}

Examples of predict functions that can be used in cross_validate_fn(). They can either be used directly or be starting points.

predict_functions(name)

name

Name of model to get predict function for, as it appears in the following table.

The Model HParams column lists hyperparameters used in the respective model function.

Name	Function	Model HParams
"lm"	`stats::lm()`
"lmer"	`lme4::lmer()`
"glm_binomial"	`stats::glm()`	`family = "binomial"`
"glmer_binomial"	`lme4::glmer()`	`family = "binomial"`
"svm_gaussian"	`e1071::svm()`	`type = "eps-regression"`
"svm_binomial"	`e1071::svm()`	`type = "C-classification"`, `probability = TRUE`
"svm_multinomial"	`e1071::svm()`	`type = "C-classification"`, `probability = TRUE`
"naive_bayes"	`e1071::naiveBayes()`
"nnet_multinom"	`nnet::multinom()`
"nnet_gaussian"	`nnet::nnet()`	`linout = TRUE`
"nnet_binomial"	`nnet::nnet()`
"randomForest_gaussian"	`randomForest::randomForest()`
"randomForest_binomial"	`randomForest::randomForest()`
"randomForest_multinomial"	`randomForest::randomForest()`

A function with the following form:

function(test_data, model, formula, hyperparameters, train_data) {

⁠ ⁠# Use model to predict test_data

⁠ ⁠# Return predictions

}