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See:
Description
| Interface Summary | |
|---|---|
| MLAutoAssocation | Defines a MLMethod that can handle autoassocation. |
| MLClassification | This interface defines a MLMethod that is used for classification. |
| MLCluster | Defines a cluster. |
| MLClustering | A machine learning method that is used to break data into clusters. |
| MLContext | Defines a MLMethod that can hold context. |
| MLEncodable | Defines a Machine Learning Method that can be encoded to a double array. |
| MLError | Defines Machine Learning Method that can calculate an error based on a data set. |
| MLInput | Defines a MLMethod that accepts input. |
| MLInputOutput | This is a convenience interface that combines MLInput and MLOutput. |
| MLMethod | This interface is the base for all Encog Machine Learning methods. |
| MLOutput | Defines a MLMethod that produces output. |
| MLProperties | Defines a Machine Learning Method that holds properties. |
| MLRegression | Defines a Machine Learning Method that supports regression. |
| MLResettable | Defines a Machine Learning Method that can be reset to an untrained starting point. |
| Class Summary | |
|---|---|
| BasicML | A class that provides basic property functionality for the MLProperties interface. |
| Enum Summary | |
|---|---|
| TrainingImplementationType | Specifies the type of training that an object provides. |
This package contains all of the classes for Machine Learning.
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