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About: A K-means clustering implementation for command-line, Python, Matlab and C. This algorithm yields the very same solution as standard Kmeans, even after each iteration. However it uses some triangle [...] Changes:Initial Announcement on mloss.org.
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About: Machine Learning PYthon (mlpy) is a high-performance Python package for predictive modeling. Changes:New features:
Several bugs fixed
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About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line. Changes:This release contains several enhancements, cleanups and bugfixes: Features
Bugfixes
Cleanup and API Changes
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About: A C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems. Changes:Minor bug fixes
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About: SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides various machine learning and computational intelligence techniques. Changes:
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About: Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, [...] Changes:0.4.4 (Mon, Feb 2 2010) (Total: 144 commits) Primarily a bugfix release, probably the last in 0.4 series since development for 0.5 release is leaping forward.
o GNB implements Gaussian Naïve Bayes Classifier. o read_fsl_design() to read FSL FEAT design.fsf files (Contributed by Russell A. Poldrack). o SequenceStats to provide basic statistics on labels sequence (counter-balancing, autocorrelation). o New exceptions DegenerateInputError and FailedToTrainError to be thrown by classifiers primarily during training/testing. o Debug target STATMC to report on progress of Monte-Carlo sampling (during permutation testing).
o To get users prepared to 0.5 release, internally and in some examples/documentation, access to states and parameters is done via corresponding collections, not from the top level object (e.g. clf.states.predictions instead of soon-to-be-deprecated clf.predictions). That should lead also to improved performance. o Adopted copy.py from python2.6 (support Ellipsis as well). ed (38 BF commits): o GLM output does not depend on the enabled states any more. o Variety of docstrings fixed and/or improved. o Do not derive NaN scaling for SVM’s C whenever data is degenerate (lead to never finishing SVM training). o sg : + KRR is optional now – avoids crashing if KRR is not available.
o Python 2.4 compatibility issues: kNN and IFS
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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 1.2.3
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About: Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Changes:Updated version to 1.0.1
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About: Classification and Regression Training Changes:Fetched by r-cran-robot on 2010-08-12 12:52:46.376590
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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...] Changes:Initial Announcement on mloss.org.
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