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About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more. Changes:Updated to version 0.3.0
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About: Toeblitz is a MATLAB/Octave package for operations on positive definite Toeplitz matrices. It can solve Toeplitz systems Tx = b in O(n*log(n)) time and O(n) memory, compute matrix inverses T^(-1) (with free log determinant) in O(n^2) time and memory, compute log determinants (without inverses) in O(n^2) time and O(n) memory, and compute traces of products A*T for any matrix A, in minimal O(n^2) time and memory. Changes:Adding a write-up in written/toeblitz.pdf describing the package.
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About: Evolutionary Learning of Globally Optimal Trees Changes:Fetched by r-cran-robot on 2014-05-01 00:00:05.459097
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About: Nieme is a C++ machine learning library for large-scale classification, regression and ranking. It provides a simple interface available in C++, Python and Java and a user interface for visualization. Changes:Released Nieme 1.0
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About: Rule- and Instance-Based Regression Modeling Changes:Fetched by r-cran-robot on 2011-08-28 08:16:03.375532
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About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. Changes:o citation update o plot function improved
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About: Regression Trees with Random Effects for Longitudinal (Panel) Data Changes:Fetched by r-cran-robot on 2013-04-01 00:00:08.040424
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About: MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to [...] Changes:MALLET 2.0 RC4 Release Notes July 16, 2009 Major updates: An implementation of generalized expectation criteria training of MaxEnt classifiers and methods for obtaining constraints (c.f. Gregory Druck, Gideon Mann, Andrew McCallum "Learning from Labeled Features using Generalized Expectation Criteria.") PagedInstanceList has been substantially rewritten by Mike Bond. Bug fixes to topic model hyperparameter optimization and topic inference.
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About: A generalized version of spectral clustering using the graph p-Laplacian. Changes:various internal optimizations
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About: RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...] Changes:Initial Announcement on mloss.org.
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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox Changes:Initial Announcement on mloss.org.
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About: Probabilistic performance evaluation for multiclass classification using the posterior balanced accuracy Changes:Added bibtex information.
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About: Scalable learning of global, multi-task and local metrics from data Changes:Minor bug fix in multi-task objective computation (thanks to Junjie Hu).
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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: Bayesian Additive Regression Trees Changes:Fetched by r-cran-robot on 2018-09-01 00:00:04.021726
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About: Generalized Boosted Regression Models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.019963
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About: LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC ), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class [...] Changes:Initial Announcement on mloss.org.
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About: A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation Changes:Release 0.7.0
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About: RLS2 is an instance of multiple kernel learning algorithm to simultaneously learn a regularized predictor and the kernel function. RLS2LIN is a version of RLS2 specialized to linear kernels on each feature. The package contains a set of scripts that implements RLS2 and RLS2LIN, together with a Graphic User Interface to load data, perform training, validation, and plot results. Changes:
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About: Classification and regression trees Changes:Fetched by r-cran-robot on 2012-02-01 00:00:11.999664
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