Uses of Package
jsat.classifiers.linear.kernelized

Packages that use jsat.classifiers.linear.kernelized

Package	Description
jsat.classifiers.linear.kernelized

Classes in jsat.classifiers.linear.kernelized used by jsat.classifiers.linear.kernelized

Class and Description
ALMA2K Provides a kernelized version of the ALMA2 algorithm.
BOGD Bounded Online Gradient Descent (BOGD) is a kernel learning algorithm that uses a bounded number of support vectors.
CSKLR An implementation of Conservative Stochastic Kernel Logistic Regression.
CSKLR.UpdateMode Controls when updates are performed on the model.
CSKLRBatch An implementation of Conservative Stochastic Kernel Logistic Regression.
DUOL Provides an implementation of Double Update Online Learning (DUOL) algorithm.
Forgetron Implementation of the first two Forgetron algorithms.
KernelSGD Kernel SGD is the kernelized counterpart to LinearSGD, and learns nonlinear functions via the kernel trick.
OSKL Online Sparse Kernel Learning by Sampling and Smooth Losses (OSKL) is an online algorithm for learning sparse kernelized solutions to binary classification problems.
Projectron An implementation of the Projectron and Projectrion++ algorithms.