ranger - A Fast Implementation of Random Forests
A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.
Last updated 3 months ago
cpp
16.21 score 778 stars 179 dependents 9.2k scripts 51k downloadssurvivalsvm - Survival Support Vector Analysis
Performs support vectors analysis for data sets with survival outcome. Three approaches are available in the package: The regression approach takes censoring into account when formulating the inequality constraints of the support vector problem. In the ranking approach, the inequality constraints set the objective to maximize the concordance index for comparable pairs of observations. The hybrid approach combines the regression and ranking constraints in the same model.
Last updated 7 years ago
5.17 score 16 stars 1 dependents 62 scripts 506 downloads