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...Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on mathematical steps. The repository includes clustering, regression, classification, neural networks, anomaly detection, and other standard ML topics. Does not rely heavily on specialized toolboxes or library shortcuts.

...A built-in graphical user interface and compound library aid in the efficient evaluation of the results. If you use ChelomEx for your research, please cite our Analytical Chemistry paper that describes the software (http://dx.doi.org/10.1021/ac503000e). To comment, send bug reports or suggestions for additional features to be implemented in future versions please send me a message. The current version ChelomEx 1.2 from 06 January 2016 includes the following changes to the original version (ChelomEx 1.0): - function to filter discovered isotope patterns after the first analysis step (isotope pattern search), accessible in the Isotope Pattern toolbar (v1.2) - updates for compatibility with MatLab versions after 2014b (v1.2) - siderophore database update (v1.1) - can now also analyze negative mode data (v1.1) - bug fixes (v1.1)