About: A comprehensive data mining environment, with a variety of machine learning components. Changes:Modifications following feedback from Knime main Author.

About: A descriptive and programming language independent format and API for the simplified configuration, documentation, and design of computer experiments. Changes:Initial Announcement on mloss.org.

About: HDDM is a python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC). Drift Diffusion Models are used widely in psychology and cognitive neuroscience to study decision making. Changes:

About: R genetic programming framework Changes:Fetched by rcranrobot on 20130401 00:00:08.163887

About: Pam Changes:Fetched by rcranrobot on 20130401 00:00:06.709586

About: Generalized linear and additive models by likelihood based boosting Changes:Fetched by rcranrobot on 20130401 00:00:04.893311

About: Classification and visualization Changes:Fetched by rcranrobot on 20130401 00:00:05.722314

About: A Toolkit for Recursive Partytioning Changes:Fetched by rcranrobot on 20130401 00:00:06.838561

About: Feedforward Neural Networks and Multinomial LogLinear Models Changes:Fetched by rcranrobot on 20130401 00:00:06.544403

About: Graphical user interface for data mining in R Changes:Fetched by rcranrobot on 20130401 00:00:07.700426

About: Regularization paths for SCAD and MCPpenalized regression models Changes:Fetched by rcranrobot on 20130401 00:00:06.449164

About: Lasso and elasticnet regularized generalized linear models Changes:Fetched by rcranrobot on 20130401 00:00:05.081872

About: The opensource Cpackage fastICA implements the fastICA algorithm of Aapo Hyvarinen et al. (URL: http://www.cs.helsinki.fi/u/ahyvarin/) to perform Independent Component Analysis (ICA) and Projection Pursuit. fastICA is released under the GNU Public License (GPL). Changes:Initial Announcement on mloss.org.

About: Heteroscedastic Discriminant Analysis Changes:Fetched by rcranrobot on 20130401 00:00:05.551691

About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, NadarayaWatson estimator); (3) generative models for random networks (smallworld, scalefree, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition. Changes:JProGraM 13.2  CHANGE LOG Release date: February 13, 2012 New features:  Support for Fiedler random graphs/random field models for largescale networks (ninofreno.graph.fiedler package);  Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).

About: Regularization paths for regression models with grouped covariates Changes:Fetched by rcranrobot on 20130401 00:00:05.489694

About: ModelBased Boosting Changes:Fetched by rcranrobot on 20130401 00:00:06.324985

About: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model Changes:Fetched by rcranrobot on 20130401 00:00:05.305206

About: Generalized Boosted Regression Models Changes:Fetched by rcranrobot on 20130401 00:00:05.019963

About: A Laboratory for Recursive Partytioning Changes:Fetched by rcranrobot on 20130401 00:00:06.775432
