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bioc

netresponse:Functional Network Analysis

Algorithms for functional network analysis. Includes an implementation of a variational Dirichlet process Gaussian mixture model for nonparametric mixture modeling.

Maintained by Leo Lahti. Last updated 5 months ago.

cellbiology clustering geneexpression genetics network graphandnetwork differentialexpression microarray networkinference transcription

3 stars 5.64 score 21 scripts

cran

randomUniformForest:Random Uniform Forests for Classification, Regression and Unsupervised Learning

Ensemble model, for classification, regression and unsupervised learning, based on a forest of unpruned and randomized binary decision trees. Each tree is grown by sampling, with replacement, a set of variables at each node. Each cut-point is generated randomly, according to the continuous Uniform distribution. For each tree, data are either bootstrapped or subsampled. The unsupervised mode introduces clustering, dimension reduction and variable importance, using a three-layer engine. Random Uniform Forests are mainly aimed to lower correlation between trees (or trees residuals), to provide a deep analysis of variable importance and to allow native distributed and incremental learning.

Maintained by Saip Ciss. Last updated 3 years ago.

cpp

4 stars 2.90 score