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KernelMethods

An opensource implementation of several kernel methods

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Kernel Methods

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

Install

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

using Pkg
pkg"add https://github.com/sadit/KernelMethods.jl"

using KernelMethods

Usage

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

Dependencies

KernelMethods.jl depends on

Final notes

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

http://docs.julialang.org/en/latest/devdocs/sysimg/

First Commit

10/11/2017

Last Touched

about 1 year ago

Commits

79 commits

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