LearnerKnn: LearnerKnn R6 class

In mlexperiments: Machine Learning Experiments

LearnerKnn R6 class

Description

This learner is a wrapper around class::knn() in order to perform a k-nearest neighbor classification.

Details

Optimization metric: classification error rate Can be used with

• MLTuneParameters

• MLCrossValidation

• MLNestedCV

Implemented methods:

• ⁠$fit⁠ To fit the model.

• ⁠$predict⁠ To predict new data with the model.

• ⁠$cross_validation⁠ To perform a grid search (hyperparameter optimization).

• ⁠$bayesian_scoring_function⁠ To perform a Bayesian hyperparameter optimization.

For the two hyperparameter optimization strategies ("grid" and "bayesian"), the parameter metric_optimization_higher_better of the learner is set to FALSE by default as the mean misclassification error (measures::MMCE()) is used as the optimization metric.

Super class

mlexperiments::MLLearnerBase -> LearnerKnn

Methods

Public methods

• LearnerKnn$new()

• LearnerKnn$clone()

Inherited methods

• mlexperiments::MLLearnerBase$bayesian_scoring_function()
• mlexperiments::MLLearnerBase$cross_validation()
• mlexperiments::MLLearnerBase$fit()
• mlexperiments::MLLearnerBase$predict()

---

Method new()

Create a new LearnerKnn object.

Usage

LearnerKnn$new()

Details

This learner is a wrapper around class::knn() in order to perform a k-nearest neighbor classification. The following experiments are implemented:

• MLTuneParameters

• MLCrossValidation

• MLNestedCV For the two hyperparameter optimization strategies ("grid" and "bayesian"), the parameter metric_optimization_higher_better of the learner is set to FALSE by default as the mean misclassification error (measures::MMCE()) is used as the optimization metric.

Examples

if (requireNamespace("class", quietly = TRUE)) {
  LearnerKnn$new()
}

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerKnn$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

class::knn(), measures::MMCE()

class::knn(), measures::MMCE()

Examples

if (requireNamespace("class", quietly = TRUE)) {
  LearnerKnn$new()
}


## ------------------------------------------------
## Method `LearnerKnn$new`
## ------------------------------------------------

if (requireNamespace("class", quietly = TRUE)) {
  LearnerKnn$new()
}

mlexperiments documentation built on Jan. 16, 2026, 5:17 p.m.