About: R/Weka interface Changes:Fetched by rcranrobot on 20120201 00:00:11.330277

About: Python module to ease pattern classification analyses of large datasets. It provides highlevel abstraction of typical processing steps (e.g. data preparation, classification, feature selection, [...] Changes:
This release aggregates all the changes occurred between official
releases in 0.4 series and various snapshot releases (in 0.5 and 0.6
series). To get better overview of high level changes see
:ref:
Also adapts changes from 0.4.6 and 0.4.7 (see corresponding changelogs).
This is a special release, because it has never seen the general public.
A summary of fundamental changes introduced in this development version
can be seen in the :ref: Most notably, this version was to first to come with a comprehensive twoday workshop/tutorial.
A bugfix release
A bugfix release

About: Bayesian treed Gaussian process models Changes:Fetched by rcranrobot on 20120201 00:00:11.834310

About: An annotated java framework for machine learning, aimed at making it really easy to access analytically functions. Changes:Now supports OLS and GLS regression and NaiveBayes classification

About: Boosting Methods for GAMLSS Models Changes:Fetched by rcranrobot on 20130401 00:00:04.956804

About: A python implementation of Breiman's Random Forests. Changes:Initial Announcement on mloss.org.

About: Survival forests: Random Forests variant for survival analysis. Original implementation by Leo Breiman. Changes:Initial Announcement on mloss.org.

About: Regression forests, Random Forests for regression. Original implementation by Leo Breiman. Changes:Initial Announcement on mloss.org.

About: The original Random Forests implementation by Breiman and Cutler. Changes:Initial Announcement on mloss.org.

About: A decision tree learner that is designed to be reasonably fast, but the primary goal is ease of use Changes:Initial Announcement on mloss.org.

About: Logic Forest Changes:Fetched by rcranrobot on 20130401 00:00:06.077571

About: The Maja Machine Learning Framework (MMLF) is a general framework for problems in the domain of Reinforcement Learning (RL) written in python. It provides a set of RL related algorithms and a set of benchmark domains. Furthermore it is easily extensible and allows to automate benchmarking of different agents. Changes:

About: Oblique Random Forests from Recursive Linear Model Splits Changes:Fetched by rcranrobot on 20120801 00:00:07.607823

About: Denoising images via normalized convolution Changes:Initial Announcement on mloss.org.

About: Classification and regression trees Changes:Fetched by rcranrobot on 20120201 00:00:11.999664

About: Bayesian Reasoning and Machine Learning toolbox Changes:Fixed some small bugs and updated some demos.

About: Regression Trees with Random Effects for Longitudinal (Panel) Data Changes:Fetched by rcranrobot on 20130401 00:00:08.040424

About: The Ktree is a scalable approach to clustering inspired by the B+tree and kmeans algorithms. Changes:Release of Ktree implementation in Python. This is targeted at a research and rapid prototyping audience.

About: A fast and scalable graphbased clustering algorithm based on the eigenvectors of the nonlinear 1Laplacian. Changes:

About: Rule and InstanceBased Regression Modeling Changes:Fetched by rcranrobot on 20110828 08:16:03.375532
