Modifier and Type | Method and Description |
---|---|
Prediction |
OnlineLearningAlgorithm.learn(Example example)
Applies the learning process on a single example, updating its current model
|
Modifier and Type | Method and Description |
---|---|
Prediction |
BudgetedLearningAlgorithm.learn(Example example) |
protected Prediction |
Stoptron.predictAndLearnWithAvailableBudget(Example example) |
protected Prediction |
RandomizedBudgetPerceptron.predictAndLearnWithAvailableBudget(Example example) |
protected abstract Prediction |
BudgetedLearningAlgorithm.predictAndLearnWithAvailableBudget(Example example) |
protected Prediction |
Stoptron.predictAndLearnWithFullBudget(Example example) |
protected Prediction |
RandomizedBudgetPerceptron.predictAndLearnWithFullBudget(Example example) |
protected abstract Prediction |
BudgetedLearningAlgorithm.predictAndLearnWithFullBudget(Example example)
Learns from a single example applying a specific policy that must be adopted when the budget is reached
|
Modifier and Type | Method and Description |
---|---|
Prediction |
PredictionFunction.predict(Example example) |
Modifier and Type | Interface and Description |
---|---|
interface |
ClassificationOutput
It is a generic output provided by a classifier
|
Modifier and Type | Class and Description |
---|---|
class |
BinaryMarginClassifierOutput
It is the output provided by binary margin classifiers like the ones trained with SVM or perceptron based
learning algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
MultiLabelClassificationOutput
It is the output provided by a multi label classifier.
|
class |
OneVsAllClassificationOutput
It is the output provided by a classifier operating in a one-vs-all schema.
|
class |
OneVsOneClassificationOutput |
Modifier and Type | Interface and Description |
---|---|
interface |
RegressionOutput
It is the output of a generic Regressor
|
Modifier and Type | Class and Description |
---|---|
class |
UnivariateRegressionOutput
It is the output of a univariate regression prediction function.
|
Modifier and Type | Method and Description |
---|---|
void |
MulticlassClassificationEvaluator.addCount(Example test,
Prediction prediction) |
abstract void |
Evaluator.addCount(Example test,
Prediction predicted)
This method should be implemented in the subclasses to update counters useful to compute the performance measure
|
void |
BinaryClassificationEvaluator.addCount(Example test,
Prediction prediction) |
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