Package | Description |
---|---|
moa.classifiers.rules | |
moa.classifiers.rules.core |
Modifier and Type | Method and Description |
---|---|
abstract RuleActiveLearningNode |
AbstractAMRules.newRuleActiveLearningNode(double[] initialClassObservations) |
RuleActiveLearningNode |
AMRulesRegressorOld.newRuleActiveLearningNode(double[] initialClassObservations) |
abstract RuleActiveLearningNode |
AbstractAMRules.newRuleActiveLearningNode(Rule.Builder builder) |
RuleActiveLearningNode |
AMRulesRegressorOld.newRuleActiveLearningNode(Rule.Builder builder) |
Modifier and Type | Method and Description |
---|---|
protected abstract Rule |
AbstractAMRules.newRule(int ID,
RuleActiveLearningNode learningNode,
double[] statistics)
Rule.Builder() to build an object with the parameters.
|
protected Rule |
AMRulesRegressorOld.newRule(int ID,
RuleActiveLearningNode node,
double[] statistics) |
Modifier and Type | Class and Description |
---|---|
class |
RuleActiveRegressionNode
A modified ActiveLearningNode that uses a Perceptron as the leaf node model,
and ensures that the class values sent to the attribute observers are not
truncated to ints if regression is being performed
|
Modifier and Type | Field and Description |
---|---|
protected RuleActiveLearningNode |
Rule.learningNode |
Modifier and Type | Method and Description |
---|---|
RuleActiveLearningNode |
Rule.getLearningNode()
getLearningNode Method This is the way to pass info for other classes.
|
Modifier and Type | Method and Description |
---|---|
abstract void |
RuleActiveLearningNode.initialize(RuleActiveLearningNode oldLearningNode) |
void |
RuleActiveRegressionNode.initialize(RuleActiveLearningNode oldLearningNode) |
void |
Rule.setLearningNode(RuleActiveLearningNode learningNode) |
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