About: KernelBased Analysis Of Biological Sequences Changes:Initial Announcement on mloss.org.

About: Cox models by likelihood based boosting for a single survival endpoint or competing risks Changes:Fetched by rcranrobot on 20141101 00:00:04.781816

About: A wrapper algorithm for allrelevant feature selection Changes:Fetched by rcranrobot on 20141101 00:00:04.390118

About: Somoclu is a massively parallel implementation of selforganizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Changes:

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. Changes:New features:  R support that is now on CRAN

About: Misc Functions of the Department of Statistics (e1071), TU Wien Changes:Fetched by rcranrobot on 20141101 00:00:04.932716

About: Classification and Regression Training Changes:Fetched by rcranrobot on 20141101 00:00:04.624779

About: Mining Association Rules and Frequent Itemsets Changes:Fetched by rcranrobot on 20141101 00:00:04.179280

About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplarbased agglomerative clustering, and various tools for visual analysis of clustering results. Changes:

About: C5.0 Decision Trees and RuleBased Models Changes:Fetched by rcranrobot on 20141101 00:00:04.543606

About: Big Random Forests Changes:Fetched by rcranrobot on 20141101 00:00:04.253859

About: Classification, regression, feature evaluation and ordinal evaluation Changes:Fetched by rcranrobot on 20141101 00:00:04.706924

About: Gradient Boosting Changes:Fetched by rcranrobot on 20141101 00:00:04.468847

About: The package "fastclime" provides a method of recover the precision matrix efficiently by applying parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method. Changes:Initial Announcement on mloss.org.

About: Estimates statistical significance of association between variables and their principal components (PCs). Changes:Initial Announcement on mloss.org.

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. It detects 100 times smaller segments than previous methods. Changes:o citation update o plot function improved

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. Changes:o citation update o plot function improved

About: Evolutionary Learning of Globally Optimal Trees Changes:Fetched by rcranrobot on 20140501 00:00:05.459097

About: Bayesian Model Averaging for linear models with a wide choice of (customizable) priors. Builtin priorss include coefficient priors (fixed, flexible and hyperg priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches. Changes:Initial Announcement on mloss.org.

About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing. Changes:CHANGES IN VERSION 2.8.0NEW FEATURES
CHANGES IN VERSION 2.4.0
CHANGES IN VERSION 2.3.1NEW FEATURES
2.0.0:
1.4.0:
