About: A general purpose library to process and predict sequences of elements using echo state networks. Changes:Initial Announcement on mloss.org.

About: "Pattern" is a web mining module for Python. It bundles tools for data retrieval, text analysis, clustering and classification, and data visualization. Changes:

About: The OrGanic Environment for Reservoir computing (Oger) toolbox is a Python toolbox for rapidly building, training and evaluating modular learning architectures on large datasets. Changes:Initial Announcement on mloss.org.

About: This package contains a python and a matlab implementation of the most widely used algorithms for multiarmed bandit problems. The purpose of this package is to provide simple environments for comparison and numerical evaluation of policies. Changes:Initial Announcement on mloss.org.

About: Nimfa is an opensource Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of stateoftheart factorization methods, initialization approaches, and quality scoring. Both dense and sparse matrix representation are supported. Changes:Initial Announcement on mloss.org.

About: mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. Changes:New features:
Fix:

About: Locally Weighted Projection Regression (LWPR) is a recent algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its [...] Changes:Version 1.2.4

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: Multicore/distributed large scale machine learning framework. Changes:Update version.

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

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: FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms we found to work best for nearest neighbor search. Changes:See project page for changes.

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: The source code of the mldata.org site  a community portal for machine learning data sets. Changes:Initial Announcement on mloss.org.

About: Tools to convert datasets from various formats to various formats, performance measures and API functions to communicate with mldata.org Changes:

About: This is the source code of the mloss.org website. Changes:Now works with newer django versions and fixes several warnings and minor bugs underneath. The only user visible change is probably that the subscription and bookmark buttons work again.

About: A chatterbot that learns natural languages learning from imitation. Changes:Alpha 1  Codename: Wendell Borton ("Bllluuhhhhh...!!") Short term memory greatly improved.

About: Epistatic miniarray profiles (EMAPs) are a highthroughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from EMAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values  up to 35%  that can reduce the effectiveness of some data analysis techniques and prevent the use of others. This project contains nearest neighbor based tools for the imputation and prediction of these missing values. The code is implemented in Python and uses a nearest neighbor based approach. Two variants are used  a simple weighted nearest neighbors, and a local least squares based regression. Changes:Initial Announcement on mloss.org.

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining. Changes:1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "scoreforclass C" causes scores to be computed relative to a given (positive) class. For twoclass problems. Fixed bug in example sampling code (sample n) Fixed bug keeping oldstyle example formats (terminated by dot) from working. More code restructuring.
