Just a simple implementation of K-Nearest Neighbour algorithm.

Related tags

Machine Learning data-science machine-learning supervised-learning knn k-nearest-neighbours supervised-machine-learning knn-classification supervised-learning-algorithms knn-classifier knn-algorithm k-nearest-neighbor-classifier supervised-learning-classifiers
Overview

A simple K-Nearest Neighbor (KNN) Java library

What is this repository for?

  • Its a very simple implementation of K-Nearest Neighbor algorithm for Supervide Learning (user labeled data)
  • Version 1.0

Features presents

  • The following similarities metrics are presents:
    • Euclidian Distance
    • Jaccard Distance
    • Pearson Correlation
    • Cosine Distance
    • Minkowski Distance (to be done)
    • Manhattan Distance (to be done)
    • Mahalanobis Distance (to be done)
  • A naive knn implementation with (or without) k-fold cross-validation.

How to use

  • Just clone the project
  • Setup your project
  • Init a SimpleKNNClassifier
  • Inject the SimilarityCalculator of your choice into SimpleKNNClassifier instance
  • Fit with some labeled data
  • Train the classifier (you can choose if you want to train using k-fold cross validation or not)
  • Pass some data to predict() method and see the label predicted
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Releases(1.0.1)
Owner
Felipe Appio
Senior Software Engineer | Tech Lead @ Zup Innovation
Felipe Appio
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