Machine Learning
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Maja Machine Learning Framework v.1.0
This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios.
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Machine Learning Tools in Java (MLJ) v.1.0
Java port and extension of MLC++ 2.
Bayes Server v.3.0
Bayes Server™ - Advanced analytical software used in the fields of Machine Learning, Time Series Analysis, Pattern Recognition, Data Mining and Artificial Intelligence.
Weka v.3.7.9
Weka packahe provides a collection of machine learning algorithms for data mining tasks.
Weka x64 v.3.7.9
Weka packahe provides a collection of machine learning algorithms for data mining tasks.
SmartDoc v.1.0.80.147
SmartDoc is a really smart way of automatically organizing your documents library - from PDF books to scanned documents and research papers.
Neural Network Component (ActiveX) v.1.0
Artificial Neural System Component is designed for researchers in the fields of machine learning, it can be used to construct Back Propagation Neural Network and to train it with provided samples, then finally recall it with appropriate data. This
SpamBlazer v.1.2.86.0
SpamBlazer for Microsoft Outlook. It uses machine learning techniques to extract pertinent rules automatically that dictate the legitimacy of an electronic email or otherwise.SpamBlazer Benefits: 1. Theoretically sound spam filtering technology; it
Simbad v.1.4
Simbad is a Java 3d robot simulator for scientific and educationnal purposes. It is mainly dedicated to researchers/programmers who want a simple basis for studying Situated Artificial Intelligence, Machine Learning, and more generally AI algorithms,
Neural Networks v.4.3.7
Create neural networks fast and easy. Inspired by neurons and their connections in the brain, neural network is a representation used in machine learning. After running the back-propagation learning algorithm on a given set of examples,
Mallet for Mac OS X v.2.0.7
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.