|
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. |
| MLStateSequence |
A state sequence ML method, for example a Hidden Markov Model. |