The Encog Machine Learning Framework

Encog is a machine learning framework in Java/C# that was developed by Jeff Heaton, a data scientist. It supports normalizing and processing data and a variety of advanced algorithm such as SVM, Neural Networks, Bayesian Networks, Hidden Markov Models, Genetic Programming, and Genetic Algorithms. It has been actively developed since 2008. It supports multi-threading, which boosts performance on multi-core systems.

It can be found at https://www.heatonresearch.com/encog/. MLMethod is the base interface, which includes all of the methods for the models. The following are some of the interfaces and classes that it includes:

• MLRegression: This interface defines regression algorithms
• MLClassification: This interface defines classification algorithms
• MLClustering: This interface defines clustering algorithms
• MLData: This class represents a vector used in a model, either for input or output
• MLDataPair: The functionality of this class is similar to that of MLData, but can be used for both input and output
• MLDataSet: This represents the list of MLDataPair instances for trainers
• FreeformNeuron: This class is used as a neuron
• FreeformConnection: This shows the weighted connection between neurons
• FreeformContextNeuron: This represents a context neuron
• InputSummation: This value specifies how the inputs are summed to form a single neuron
• BasicActiveSummation: This is the simple sum of all input neurons
• BasicFreeConnection: This is the basic weighted connection between neurons
• BasicFreeformLayer: This interface provides a layer