About: [FACTORIE](http://factorie.cs.umass.edu) is a toolkit for deployable probabilistic modeling, implemented as a software library in [Scala](http://scalalang.org). It provides its users with a succinct language for creating [factor graphs](http://en.wikipedia.org/wiki/Factor_graph), estimating parameters and performing inference. It also has implementations of many machine learning tools and a full NLP pipeline. Changes:Initial Announcement on mloss.org.

About: Dataefficient policy search framework using probabilistic Gaussian process models Changes:Initial Announcement on mloss.org.

About: PRoNTo is freely available software and aims to facilitate the interaction between the neuroimaging and machine learning communities. The toolbox is based on pattern recognition techniques for the analysis of neuroimaging data. PRoNTo supports the analysis of all image modalities as long as they are NIfTI format files. However, only the following modalites have been tested for version 1.1: sMRI, fMRI, PET, FA (fractional anisotropy) and Beta (GLM coefficients) images. Changes:Initial Announcement on mloss.org.

About: Approximate Rank One FACtorization of tensors. An algorithm for factorization of threewaytensors and determination of their rank, includes example applications. Changes:Initial Announcement on mloss.org.

About: This is the core MCMC sampler for the nonparametric sparse factor analysis model presented in David A. Knowles and Zoubin Ghahramani (2011). Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling. Annals of Applied Statistics Changes:Initial Announcement on mloss.org.

About: Regularization paTH for LASSO problem (thalasso) thalasso solves problems of the following form: minimize 1/2X*betay^2 + lambda*sumbeta_i, where X and y are problem data and beta and lambda are variables. Changes:Initial Announcement on mloss.org.

About: Regularization for semiparametric additive hazards regression Changes:Fetched by rcranrobot on 20160501 00:00:03.866271

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in:  Ellipsoidal multiple instance learning  difference of convex functions algorithms for sparse classfication  Contextual bandits upper confidence bound algorithm (using GP)  learning output kernels, that is kernels between the labels of a classifier. Changes:

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
