| Package | Description |
|---|---|
| gov.sandia.cognition.learning.algorithm.ensemble |
Provides ensemble methods.
|
| Modifier and Type | Class and Description |
|---|---|
class |
BaggingCategorizerLearner<InputType,CategoryType>
Learns an categorization ensemble by randomly sampling with replacement
(duplicates allowed) some percentage of the size of the data (defaults to
100%) on each iteration to train a new ensemble member.
|
class |
BaggingRegressionLearner<InputType>
Learns an ensemble for regression by randomly sampling with replacement
(duplicates allowed) some percentage of the size of the data (defaults to
100%) on each iteration to train a new ensemble member.
|
class |
BinaryBaggingLearner<InputType>
The
BinaryBaggingLearner implements the Bagging learning algorithm. |
class |
CategoryBalancedBaggingLearner<InputType,CategoryType>
An extension of the basic bagging learner that attempts to sample bags that
have equal numbers of examples from every category.
|