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 aKNN
classifieroptimize!
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