Showing Items 221-240 of 676 on page 12 of 34: First Previous 7 8 9 10 11 12 13 14 15 16 17 Next Last
About: This toolbox implements models for Bayesian mixed-effects inference on classification performance in hierarchical classification analyses. Changes:In addition to the existing MATLAB implementation, the toolbox now also contains an R package of the variational Bayesian algorithm for mixed-effects inference.
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About: Infrastructure for representing, manipulating and analyzing transaction data and frequent patterns. Changes:Initial Announcement on mloss.org.
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About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'. Changes:Moved project to GitHub.
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About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; One-shot training for an entire regularization path; Continuous checkpointing; much more Changes:
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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: A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation Changes:Release 0.7.0
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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: Least Angle Regression, Lasso and Forward Stagewise Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.906244
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About: Document/Text preprocessing for topic models: suite of Perl scripts for preprocessing text collections to create dictionaries and bag/list files for use by topic modelling software. Changes:Moved distribution and code across to GitHub. Changed "ldac" format to have 0 offset for word indices. Added "document frequency" (df) filtering on selection of tokens for linkTables. Playing with linkParse but its still unuseable generally.
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About: The Easysvm package provides a set of tools based on the Shogun toolbox allowing to train and test SVMs in a simple way. Changes:Fixes for shogun 0.7.3.
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About: LibSGDQN proposes an implementation of SGD-QN, a carefully designed quasi-Newton stochastic gradient descent solver for linear SVMs. Changes:small bug fix (thx nicolas ;)
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About: A Matlab script for learning vector-valued functions and kernels on the output space. Changes:Added code for learning low-rank output kernels.
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About: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.305206
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About: ALGLIB is an open source numerical analysis library distributed under GPL 2+. It implements both general numerical algorithms and machine learning algorithms. ALGLIB can be used from C#, C++, FreePascal, VBA and other languages. It is the only numerical analysis library which uses automatic translation to generate source code written in different programming languages with 100% identical functionality. Changes:
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About: Trees WIth eXtra splits Changes:Fetched by r-cran-robot on 2012-02-01 00:00:12.077735
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About: An audio editing tool for single-channel source separation. Changes:Stereo processing, bug fixes, UI updates.
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About: A comprehensive data mining environment, with a variety of machine learning components. Changes:Modifications following feedback from Knime main Author.
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About: Torch5 provides a matlab-like environment for state-of-the-art machine learning algorithms. It is easy to use and provides a very efficient implementation, thanks to a easy and fast scripting [...] Changes:Initial Announcement on mloss.org.
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