Search Results for "random forest"

...You can also download SPiP in zip format: https://sourceforge.net/projects/splicing-prediction-pipeline/files/SPiP_alone_v2_1.zip For Linux (GitHub): https://github.com/LBGC-CFB/SPiP If you have questions, please contact me to: r.leman@baclesse.unicancer.fr or raphael.leman@orange.fr v2.1 corrected (07/2021) : correction of score calculation v2.1 (06/2021): Most strigent on "Alter by complex event" v2.0 (04/2021): New SPiP with random forest modelization old change detailled in https://sourceforge.net/projects/splicing-prediction-pipeline/files/changeLogBeforev2.0.txt

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.

A machine learning-based method for somatic variant identification from low-pass next-generation sequencing.

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.

The package implements a variety of tools for categorization of multivariate data such as boosted decision trees, bagging and random forest, bump hunting (PRIM), a multi-class learner and others.