Uses of Class
jsat.classifiers.BaseUpdateableClassifier

Packages that use BaseUpdateableClassifier

Package	Description
jsat.classifiers
jsat.classifiers.bayesian
jsat.classifiers.linear
jsat.classifiers.linear.kernelized
jsat.classifiers.svm.extended

Uses of BaseUpdateableClassifier in jsat.classifiers

Constructors in jsat.classifiers with parameters of type BaseUpdateableClassifier

Constructor and Description
BaseUpdateableClassifier(BaseUpdateableClassifier toCopy) Copy constructor

Uses of BaseUpdateableClassifier in jsat.classifiers.bayesian

Subclasses of BaseUpdateableClassifier in jsat.classifiers.bayesian

Modifier and Type	Class and Description
class	AODE Averaged One-Dependence Estimators (AODE) is an extension of Naive Bayes that attempts to be more accurate by reducing the independence assumption.
class	MultinomialNaiveBayes An implementation of the Multinomial Naive Bayes model (MNB).
class	NaiveBayesUpdateable An implementation of Gaussian Naive Bayes that can be updated in an online fashion.
class	ODE One-Dependence Estimators (ODE) is an extension of Naive Bayes that, instead of assuming all features are independent, assumes all features are dependent on one other feature besides the target class.

Uses of BaseUpdateableClassifier in jsat.classifiers.linear

Subclasses of BaseUpdateableClassifier in jsat.classifiers.linear

Modifier and Type	Class and Description
class	ALMA2 Provides a linear implementation of the ALMAp algorithm for p = 2, which is considerably more efficient to compute.
class	AROW An implementation of Adaptive Regularization of Weight Vectors (AROW), which uses second order information to learn a large margin binary classifier.
class	LinearSGD LinearSGD learns either a classification or regression problem depending on the loss function ℓ(w,x) used.
class	NHERD Implementation of the Normal Herd (NHERD) algorithm for learning a linear binary classifier.
class	ROMMA Provides an implementation of the linear Relaxed online Maximum Margin algorithm, which finds a similar solution to SVMs.
class	SCW Provides an Implementation of Confidence-Weighted (CW) learning and Soft Confidence-Weighted (SCW), both of which are binary linear classifiers inspired by PassiveAggressive.
class	SPA Support class Passive Aggressive (SPA) is a multi class generalization of PassiveAggressive.
class	STGD This provides an implementation of Sparse Truncated Gradient Descent for L1 regularized linear classification and regression on sparse data sets.

Uses of BaseUpdateableClassifier in jsat.classifiers.linear.kernelized

Subclasses of BaseUpdateableClassifier in jsat.classifiers.linear.kernelized

Modifier and Type	Class and Description
class	ALMA2K Provides a kernelized version of the ALMA2 algorithm.
class	BOGD Bounded Online Gradient Descent (BOGD) is a kernel learning algorithm that uses a bounded number of support vectors.
class	CSKLR An implementation of Conservative Stochastic Kernel Logistic Regression.
class	DUOL Provides an implementation of Double Update Online Learning (DUOL) algorithm.
class	Forgetron Implementation of the first two Forgetron algorithms.
class	OSKL Online Sparse Kernel Learning by Sampling and Smooth Losses (OSKL) is an online algorithm for learning sparse kernelized solutions to binary classification problems.
class	Projectron An implementation of the Projectron and Projectrion++ algorithms.

Uses of BaseUpdateableClassifier in jsat.classifiers.svm.extended

Subclasses of BaseUpdateableClassifier in jsat.classifiers.svm.extended

Modifier and Type	Class and Description
class	AMM This is the batch variant of the Adaptive Multi-Hyperplane Machine (AMM) algorithm.
class	OnlineAMM This is the Online variant of the Adaptive Multi-Hyperplane Machine (AMM) algorithm.