An opensource implementation of several kernel methods
Author sadit
1 Star
Updated Last
4 Years Ago
Started In
October 2017

Build Status Coverage Status codecov

Kernel Methods

KernelMethods.jl is a library that implements and explores Kernel-Based Methods for supervised learning and semi-supervised learning.


To start using KernelMethods.jl just type into an active Julia session

using Pkg

using KernelMethods


KernelMethods.jl consists of the following parts

  • Scores. It contains several common performance measures, i.e., accuracy, recall, precision, f1, precision_recall.
  • CrossValidation. Some methods to perform cross validation, all of them work through callback functions:
    • montecarlo
    • kfolds
  • Supervised. It contains methods related to supervised learning
    • NearNeighborClassifier. It defines a KNN classifier
    • optimize!
    • predict
    • predict_proba

Note: user defined distance functions are accepted; several common distances can be found in SimilaritySearch.jl


KernelMethods.jl depends on

Final notes

To reach maximum performance, please ensure that Julia has access to the specific instruction set of your CPUs

Used By Packages

No packages found.