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PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.
This project implements in Python some common statistical analysis methods used in data analysis, including Entropy, Mutual Information, Kolmogorov–Smirnov test, Kullback-Leibler divergence (KLD), AB tests (Mann-Whitney U and t-tests)
writR: is an R package for automated inferential testing (for group differences) and reporting based on parametric assumptions, which are tested automatically for test selection.
Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.