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https://github.com/jeanbou/tdts

Matlab based Ph.D. project T-DTS, developed during for the thesis 2006-2009. It's the enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) structure-based tool used for classification tasks. The credits: the v.1.0 was developed by Dr. M. Rybnik under supervision of Prof. K. Madani
https://github.com/jeanbou/tdts

ai ann artificial-intelligence artificial-neural-networks big-data bigdata classification classification-algorithm classification-trees coding decomposition ibm-neuro-computer love machine-learning t-dts tdts treelikedividetosimplify zisc zisc-036

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Matlab based Ph.D. project T-DTS, developed during for the thesis 2006-2009. It's the enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) structure-based tool used for classification tasks. The credits: the v.1.0 was developed by Dr. M. Rybnik under supervision of Prof. K. Madani

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# T-DTS (Tree-like Divide to Simplify)

*T-DTS (Tree-like Divide to Simplify)* is a next software *version 3.0* writen in Matlab 6 in the scope of *my thesis*:
["Contribution to the Study and Implementation of Intelligent Modular Self-organizing Systems"](https://www.theses.fr/144154781)

The beta *version 2.0* was initially developed by [*Dr. M. Rybnik*](https://www.researchgate.net/profile/Mariusz-Rybnik-2)

The development was accomplished under supervision of [*Prof. K. Madani*](https://www.researchgate.net/profile/Kurosh-Madani) and [*Prof. A. Chebira*](https://www.researchgate.net/profile/Abdennasser-Chebira)

My enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) lego-like tool used for any classification task which is grounded on the following ideas:
* The set of DB classification decomposers and the set of the end-tree-leaf classifiers (*Rybnik's implementation in code + his T-DTS code skeleton*)
* Increased library of classification task complexety estimators (*Rybnik's and my contributions plus a lot of debug*)
* Among them [RBF Net](https://en.wikipedia.org/wiki/Radial_basis_function_network) like [IBM ZISC(r)-036 RBF Net](https://en.wikipedia.org/wiki/No_instruction_set_computing#Zero_instruction_set_computer) based estimator that allows us to build T-TDS on chip (*my contribution*)
* Extra loop that allows us to find sub-optimal classification complexity estimator from lib based on max entropy principle and define its optimal value for a concrete classification problem as there is no absolute value and no approach for end-user to guess apriory except try, check, fail & try again approach (*my contribution*)