RSS Feed - Blog
About: PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined [...] Changes:
|
About: A Java framework for statistical analysis and classification of biological sequences Changes:March 2, 2010: Jstacs 1.3.1 released
|
About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values. Changes:-) Feature ranking algorithm added (fss.m) -) train_sc: {-1,+1}-encoding of classlabels supported weighted liblinear and svm source code included add "Deletion"-Mode: this enables NaN-support for training algorithms that did not have support for data with SVM (liblinear, SVM, etc.) -) str2double.mex for fast decoding of delimiter files. -) bug fixes (train_sc PLA) Some minor bug fixes. For details see: http://biosig-consulting.com/matlab/NaN/CHANGELOG
|
About: The K-tree is a scalable approach to clustering inspired by the B+-tree and k-means algorithms. Changes:Initial Announcement on mloss.org.
|
About: The JINSECT toolkit is a Java-based toolkit and library that supports and demonstrates the use of n-gram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classi?cation and indexing. Changes:
|
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
|
|
About: Given many points in ROC (Receiver Operator Characteristics) space, computes the convex hull. Changes:Initial Announcement on mloss.org.
|
About: Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...] Changes:Focus on performance and cleanup of APIs on the way to a 1.0 release. Added several new algorithms (LDA, Frequent Patternset Mining, Random Decision Forests). See 0.2 release announcement: http://lucene.apache.org/mahout/index.html#17+Nov.+2009+-+Apache+Mahout+0.2+released
|
About: Python Machine Learning Toolkit Changes:Improved Performance. Removed files from the distribution that were mistakenly included.
|
About: DAL is an efficient and flexibible MATLAB toolbox for sparse learning/reconstruction based on the augmented Lagrangian method. Changes:
|
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:Initial Announcement on mloss.org.
|
About: A (randomized) coordinate descent procedure to minimize L1 regularized loss for classification and regression purposes. Changes:Fixed some I/O bugs. Lines that ended with whitespace were not read correctly in the previous version.
|
About: A dependency parser with integer linear programming Changes:Initial Announcement on mloss.org.
|
About: Trees WIth eXtra splits Changes:Fetched by r-cran-robot on 2009-11-17 07:16:07.610679
|
About: Pam Changes:Fetched by r-cran-robot on 2009-11-17 07:16:06.365113
|
About: Improved Predictors Changes:Fetched by r-cran-robot on 2009-11-17 07:16:05.512460
|
About: Multivariate Adaptive Regression Spline Models Changes:Fetched by r-cran-robot on 2009-11-17 07:16:04.877246
|
About: Classification and visualization Changes:Fetched by r-cran-robot on 2009-11-17 07:16:05.680826
|
About: Misc Functions of the Department of Statistics (e1071), TU Wien Changes:Fetched by r-cran-robot on 2009-11-17 07:16:04.736021
|