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GAKNN is a data mining software for gene annotation data. GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.
A utility to extract data from RDBMSs and convert into .arff file format required by WEKA data mining tool set, both interactive wizard and batch working modes.
A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.
ktdata is a C++ library for accessing tabular data, like from CSV files. Its goals are:
1. object design
2. portability (Linux and Windows support at least)
3. high performance
4. support for common data file formats, like CSV, ARFF (Weka), etc.