Weka is the Machine Learning Software in Java.
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
Weka is open source software issued under the GNU General Public License.
Reviews of Weka
1. WekatextToXML 0.1.7 Weka is a complete and user-friendly data-mining environment that can be used for any research project. But Weka decision tree classifiers outputs the decision tree either as a Weka-syntaxed text tree or as a binary file (neither readable nor... Details - Download - Screenshot
2. Weka x64 3.7.8 Weka packahe provides a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification,... Details - Download - Screenshot
3. weka neural network algorithms 1.0.3 This project contains Weka packages of neural networks algorithms implementations like Learning Vector Quantizer (LVQ) and Self-organizing Maps (SOM). For more information about Weka, please visit http://www.cs.waikato.ac.nz/~ml/Weka/ Details - Download
4. weka outlier b Weka outlier is an implementation of outlier detection algorithms for Weka. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using Weka framework. Details - Download
6. Java Neural Network Framework Neuroph 2.7 Neuroph is friendly Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and nice GUI make it easy to learn and use. Details - Download - Screenshot
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