object

knn

k-Nearest Neighbors classifier with multiple distance metrics and weighting options. Learns from a dataset object implementing the dataset_protocol protocol and returns a classifier term that can be used for prediction and exported as predicate clauses.

Availability:
logtalk_load(knn(loader))
Author: Paulo Moura
Version: 1:0:0
Date: 2026-02-20
Compilation flags:
static, context_switching_calls
Implements:
public classifier_protocol
Imports:
public options
Uses:
format
list
pairs
type
Remarks:

  • Algorithm: k-NN is a lazy learning algorithm that classifies instances based on the majority class among the k nearest training instances.

  • Distance metrics: Supports Euclidean, Manhattan, Chebyshev, and Minkowski distance metrics.

  • Weighting schemes: Supports uniform, distance-based, and Gaussian weighting of neighbors.

  • Feature types: Automatically handles numeric and categorical features.

  • Classifier representation: The learned classifier is represented (by default) as a knn_classifier(AttributeNames, FeatureTypes, Instances) where Instances contains the training data.

Inherited public predicates:
 check_option/1  check_options/1  classifier_to_clauses/4  classifier_to_file/4  default_option/1  default_options/1  learn/2  option/2  option/3  predict/3  print_classifier/1  valid_option/1  valid_options/1

Public predicates

predict/4

Predicts the class label for a new instance using the learned classifier and the given options. The instance is a list of Attribute-Value pairs.

Compilation flags:
static
Template:
predict(Classifier,Instance,Class,Options)
Mode and number of proofs:
predict(+compound,+list,-atom,+list(compound)) - one

predict_probabilities/3

Predicts class probabilities for a new instance using the learned classifier and default options. Returns a list of Class-Probability pairs. The instance is a list of Attribute-Value pairs.

Compilation flags:
static
Template:
predict_probabilities(Classifier,Instance,Probabilities)
Mode and number of proofs:
predict_probabilities(+compound,+list,-list) - one

predict_probabilities/4

Predicts class probabilities for a new instance using the learned classifier and the given options. Returns a list of Class-Probability pairs. The instance is a list of Attribute-Value pairs.

Compilation flags:
static
Template:
predict_probabilities(Classifier,Instance,Probabilities,Options)
Mode and number of proofs:
predict_probabilities(+compound,+list,-list,+list(compound)) - one

Protected predicates

(no local declarations; see entity ancestors if any)

Private predicates

(no local declarations; see entity ancestors if any)

Operators

(none)

See also

dataset_protocol, c45, isolation_forest, naive_bayes, nearest_centroid, random_forest, ada_boost