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Encog Machine Learning Framework

Jeff's BLOG

Encog is an advanced machine learning framework that supports a variety of advanced algorithms, as well as support classes to normalize and process data. Machine learning algorithms such as Support Vector Machines, Artificial Neural Networks, Genetic Programming, Bayesian Networks, Hidden Markov Models and Genetic Algorithms are supported. Most Encog training algoritms are multi-threaded and scale well to multicore hardware. Encog can also make use of a GPU to further speed processing time. A GUI based workbench is also provided to help model and train machine learning algorithms. Encog has been in active development since 2008.

Encog is available for Java, .Net and C/C++.

Machine Learning

  • Bayesian Networks
  • Clustering
  • Genetic Algorithms
  • Hidden Markov Models
  • Neural Networks
  • Particle Swarm Optimization
  • Simulated Annealing
  • Support Vector Machines

Neural Network Architectures

  • ADALINE Neural Network
  • Adaptive Resonance Theory 1 (ART1)
  • Bidirectional Associative Memory (BAM)
  • Boltzmann Machine
  • Counterpropagation Neural Network (CPN)
  • Elman Recurrent Neural Network
  • Feedforward Neural Network (Perceptron)
  • Hopfield Neural Network
  • Jordan Recurrent Neural Network
  • Neuroevolution of Augmenting Topologies (NEAT)
  • Radial Basis Function Network
  • Recurrent Self Organizing Map (RSOM)
  • Self Organizing Map (Kohonen)

Training Techniques

  • ADALINE Training
  • Backpropagation
  • Competitive Learning
  • Genetic Algorithm Training
  • Hopfield Learning
  • Instar & Outstar Training
  • Levenberg Marquardt (LMA)
  • Manhattan Update Rule Propagation
  • Nelder Mead Training
  • Particle Swarm (PSO) Training
  • Resilient Propagation (RPROP)
  • Scaled Conjugate Gradient (SCG)

Data Models

  • Supervised
  • Unsupervised
  • Temporal (Prediction)
  • Financial (downloads from Yahoo Finance)
  • SQL
  • XML
  • CSV
  • Image Downsampling

Randomization Techniques

  • Range Randomization
  • Gaussian Random Numbers
  • Fan-In
  • Nguyen-Widrow

    Activation Functions

    • Bipolar
    • Competitive
    • Elliott
    • Gaussian
    • Hyperbolic Tangent
    • Linear
    • Sin Wave
    • Sigmoid
    • SoftMax
    • Step
    • Tangential

    Other Projects

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