Uses of Class
edu.illinois.cs.cogcomp.lbjava.learn.LinearThresholdUnit

Packages that use LinearThresholdUnit

Package	Description
edu.illinois.cs.cogcomp.lbjava.learn

Uses of LinearThresholdUnit in edu.illinois.cs.cogcomp.lbjava.learn

Subclasses of LinearThresholdUnit in edu.illinois.cs.cogcomp.lbjava.learn

Modifier and Type	Class and Description
class	BinaryMIRA The Binary MIRA learning algorithm implementation.
class	PassiveAggressive The Passive Aggressive learning algorithm implementation.
class	SparseAveragedPerceptron An approximation to voted Perceptron, in which a weighted average of the weight vectors arrived at during training becomes the weight vector used to make predictions after training.
class	SparseConfidenceWeighted This is an implementation of the approximate "variance algorithm" of Confidence Weighted Linear Classification, Dredze, et.al (ICML, 2008).
class	SparsePerceptron Simple sparse Perceptron implementation.
class	SparseWinnow Simple sparse Winnow implementation.

Fields in edu.illinois.cs.cogcomp.lbjava.learn declared as LinearThresholdUnit

Modifier and Type	Field and Description
protected LinearThresholdUnit	SparseNetworkLearner.baseLTU The underlying algorithm used to learn each class separately as a binary classifier; default SparseNetworkLearner.defaultBaseLTU.
LinearThresholdUnit	SparseNetworkLearner.Parameters.baseLTU The underlying algorithm used to learn each class separately as a binary classifier; default SparseNetworkLearner.defaultBaseLTU.
static LinearThresholdUnit	SparseNetworkLearner.defaultBaseLTU Default for SparseNetworkLearner.baseLTU.

Methods in edu.illinois.cs.cogcomp.lbjava.learn that return LinearThresholdUnit

Modifier and Type	Method and Description
LinearThresholdUnit	SparseNetworkLearner.getBaseLTU()

Methods in edu.illinois.cs.cogcomp.lbjava.learn with parameters of type LinearThresholdUnit

Modifier and Type	Method and Description
void	SparseNetworkLearner.setLTU(LinearThresholdUnit ltu) Sets the baseLTU variable.

Constructors in edu.illinois.cs.cogcomp.lbjava.learn with parameters of type LinearThresholdUnit

Constructor and Description
MultiLabelLearner(LinearThresholdUnit ltu) Instantiates this multi-label learner using the specified algorithm to learn each class separately as a binary classifier.
MultiLabelLearner(String n, LinearThresholdUnit ltu) Instantiates this multi-label learner using the specified algorithm to learn each class separately as a binary classifier.
SparseNetworkLearner(LinearThresholdUnit ltu) Instantiates this multi-class learner using the specified algorithm to learn each class separately as a binary classifier.
SparseNetworkLearner(String n, LinearThresholdUnit ltu) Instantiates this multi-class learner using the specified algorithm to learn each class separately as a binary classifier.