| Modifier and Type | Interface and Description |
|---|---|
interface |
BinaryLearningAlgorithm
It is a learning algorithm that has to learn a concept associated to a single label.
|
interface |
EnsembleLearningAlgorithm
It is an ensemble method that operates combining various learning algorithms
|
interface |
MetaLearningAlgorithm
It is a meta algorithm that operates modifying exploiting another learning algorithm
|
interface |
OnlineLearningAlgorithm
It is a Machine Learning algorithm which allows an incremental learning strategy, exploiting a single Example
at a time
|
| Modifier and Type | Class and Description |
|---|---|
class |
MultiEpochLearning
It is a meta learning algorithms for online learning methods.
|
class |
PassiveAggressive
It is an online learning algorithms that implements the Passive Aggressive algorithms described in
[Crammer, JMLR2006] K.
|
| Modifier and Type | Method and Description |
|---|---|
LearningAlgorithm |
LearningAlgorithm.duplicate()
Creates a new instance of the LearningAlgorithm initialized with the same parameters
of the learningAlgorithm to be duplicated.
|
LearningAlgorithm |
MetaLearningAlgorithm.getBaseAlgorithm()
Returns the base algorithm this meta algorithm is based on
|
LearningAlgorithm |
MultiEpochLearning.getBaseAlgorithm() |
| Modifier and Type | Method and Description |
|---|---|
List<LearningAlgorithm> |
EnsembleLearningAlgorithm.getToCombine()
Returns a list of the learning algorithm this ensemble method is combining
|
| Modifier and Type | Method and Description |
|---|---|
void |
MetaLearningAlgorithm.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) |
void |
MultiEpochLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) |
| Modifier and Type | Method and Description |
|---|---|
void |
EnsembleLearningAlgorithm.setToCombine(List<LearningAlgorithm> toCombine) |
| Constructor and Description |
|---|
MultiEpochLearning(int epochs,
LearningAlgorithm baseAlgorithm,
List<Label> labels) |
| Modifier and Type | Class and Description |
|---|---|
class |
BudgetedLearningAlgorithm
It is binary kernel-based online learning method that binds the number of support vector to a fix number (i.e.
|
class |
RandomizedBudgetPerceptron
It is a variation of the Randomized Budget Perceptron proposed in
|
class |
Stoptron
It is a variation of the Stoptron proposed in
|
| Modifier and Type | Method and Description |
|---|---|
void |
Stoptron.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) |
void |
RandomizedBudgetPerceptron.setBaseAlgorithm(LearningAlgorithm baseAlgorithm) |
| Modifier and Type | Interface and Description |
|---|---|
interface |
ClassificationLearningAlgorithm
It is a generic Machine Learning algorithm for Classification tasks
|
| Modifier and Type | Class and Description |
|---|---|
class |
LibLinearLearningAlgorithm
This class implements linear SVMs models trained using a coordinate descent
algorithm [Fan et al, 2008].
|
| Modifier and Type | Class and Description |
|---|---|
class |
BinaryCSvmClassification
It implements the C-SVM learning algorithm discussed in [CC Chang & CJ Lin,
2011].
|
class |
BinaryNuSvmClassification
It implements the \(\nu\)-SVM learning algorithm discussed in [CC Chang & CJ
Lin, 2011].
|
class |
OneClassSvmClassification
It implements the One class SVM learning algorithm discussed in [CC Chang &
CJ Lin, 2011].
|
| Modifier and Type | Class and Description |
|---|---|
class |
LibCSvmSolver
This class implements the solver of the C-SVM quadratic problem described in
[CC Chang & CJ Lin, 2011].
|
class |
LibNuSvmSolver
It is the instance of a solution provided the \(\nu\)-SVM solver of the
optimization problem.
|
class |
LibSvmSolver
This class implements the solver of the SVM quadratic problem described in
[CC Chang & CJ Lin, 2011].
|
| Modifier and Type | Class and Description |
|---|---|
class |
MultiLabelClassificationLearning
It is a meta algorithm that operates applying a multi label learning strategy over the base
learning algorithm which is intended to be a binary learner.
|
class |
OneVsAllLearning
It is a meta algorithm that operates applying a One-Vs-All strategy over the base
learning algorithm which is intended to be a binary learner.
|
class |
OneVsOneLearning
It is a meta algorithm that operates by applying a One-Vs-One strategy over the base
learning algorithm which is intended to be a binary learner.
|
| Modifier and Type | Method and Description |
|---|---|
LearningAlgorithm |
OneVsOneLearning.getBaseAlgorithm()
This method will return the base algorithm.
|
LearningAlgorithm |
OneVsAllLearning.getBaseAlgorithm()
This method will return the base algorithm.
|
LearningAlgorithm |
MultiLabelClassificationLearning.getBaseAlgorithm()
This method will return the base algorithm.
|
| Modifier and Type | Method and Description |
|---|---|
void |
OneVsOneLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
This method will set the type of the base algorithms to be learned.
|
void |
OneVsAllLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
This method will set the type of the base algorithms to be learned.
|
void |
MultiLabelClassificationLearning.setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
This method will set the type of the base algorithms to be learned.
|
| Modifier and Type | Class and Description |
|---|---|
class |
BudgetedPassiveAggressiveClassification
Online Passive-Aggressive on a budget
reference: Zhuang Wang and Slobodan Vucetic
Online Passive-Aggressive Algorithms on a Budget
|
class |
KernelizedPassiveAggressiveClassification
Online Passive-Aggressive Learning Algorithm for classification tasks (Kernel Machine version) .
|
class |
LinearPassiveAggressiveClassification
Online Passive-Aggressive Learning Algorithm for classification tasks (linear version) .
|
class |
PassiveAggressiveClassification
Online Passive-Aggressive Learning Algorithm for classification tasks.
|
| Modifier and Type | Method and Description |
|---|---|
LearningAlgorithm |
BudgetedPassiveAggressiveClassification.duplicate() |
| Modifier and Type | Class and Description |
|---|---|
class |
PegasosLearningAlgorithm
It implements the Primal Estimated sub-GrAdient SOlver (PEGASOS) for SVM.
|
| Modifier and Type | Class and Description |
|---|---|
class |
KernelizedPerceptron
The perceptron learning algorithm algorithm for classification tasks (Kernel machine version).
|
class |
LinearPerceptron
The perceptron learning algorithm algorithm for classification tasks (linear version).
|
class |
Perceptron
The perceptron learning algorithm algorithm for classification tasks.
|
| Modifier and Type | Interface and Description |
|---|---|
interface |
RegressionLearningAlgorithm
It is a learning algorithm that learn how to solve a generic regression task
|
| Modifier and Type | Class and Description |
|---|---|
class |
LibLinearRegression
This class implements linear SVM regression trained using a coordinate descent
algorithm [Fan et al, 2008].
|
| Modifier and Type | Class and Description |
|---|---|
class |
EpsilonSvmRegression
It implements the \(\epsilon\)-SVR learning algorithm discussed in [CC Chang
& CJ Lin, 2011].
|
| Modifier and Type | Class and Description |
|---|---|
class |
KernelizedPassiveAggressiveRegression
Online Passive-Aggressive Learning Algorithm for regression tasks (kernel machine version).
|
class |
LinearPassiveAggressiveRegression
Online Passive-Aggressive Learning Algorithm for regression tasks (linear version).
|
class |
PassiveAggressiveRegression
Online Passive-Aggressive Learning Algorithm for regression tasks.
|
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