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Showing 2 open source projects for "forest"
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This application allow user to predict dissolution profile of solid dispersion systems based on algorithms like symbolic regression, deep neural networks, random forests or generalized boosted models. Those techniques can be combined to create expert system. Application was created as a part of project K/DSC/004290 subsidy for young researchers from Polish Ministry of Higher Education.
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RF++ is a Random Forest-based classifier. It can classify cluster-correlated non-independent data in a statistically valid fashion. RF++ also identifies important variables (biomarkers) in datasets with large numbers of variables and few subjects.
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