Description:

OpenANN provides

• Various types of artificial neural networks: multilayer neural network, convolutional neural network (CNN) with convolutional layers, subsampling layers and max-pooling layers, random projections for data and network compression and extreme learning machines, restricted Boltzmann machines (RBM) and sparse auto-encoders (SAE) for unsupervised pretraining
• Optimization algorithms: mini-batch stochastic gradient descent (MBSGD) for large networks, conjugate gradient (CG) for large networks, limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) and Levenberg-Marquardt algorithm (LMA) for smaller networks, (increasing population size) covariance matrix adaption evolution strategies (IPOPCMAES) for reinforcement learning
• Supported languages: C++, Python bindings

Changes to previous version:

Added algorithms:

• L-BFGS optimizer
• k-means
• sparse auto-encoder
• preprocessing: normalization, PCA, ZCA whitening

BibTeX Entry: Download

Supported Operating Systems: Linux, Macos

Data Formats: Numpy, Libsvm, Fann

Tags: Neural Networks

Archive: download here

Other available revisons

Version	Changelog	Date
1.1.0	Added algorithms: L-BFGS optimizer k-means sparse auto-encoder preprocessing: normalization, PCA, ZCA whitening	September 26, 2013, 23:52:03
1.0.0	Initial Announcement on mloss.org.	June 22, 2013, 19:34:01

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