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 pkg"add https://github.com/sadit/KernelMethods.jl" 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:
- Supervised. It contains methods related to supervised learning
NearNeighborClassifier. It defines a
Note: user defined distance functions are accepted; several common distances can be found in
KernelMethods.jl depends on
To reach maximum performance, please ensure that Julia has access to the specific instruction set of your CPUs