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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 "--score-for-class C" causes scores to be computed relative to a given (positive) class. For two-class problems. Fixed bug in example sampling code (--sample n) Fixed bug keeping old-style example formats (terminated by dot) from working. More code restructuring.
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About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.
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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: Generalized linear and additive models by likelihood based boosting Changes:Fetched by r-cran-robot on 2013-04-01 00:00:04.893311
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About: libnabo is a fast K Nearset Neighbor library for low-dimensional spaces. Changes:
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About: This package contains a python and a matlab implementation of the most widely used algorithms for multi-armed 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.
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About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast. Changes:Changes from 1.0:
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About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing. Changes:CHANGES IN VERSION 2.8.0NEW FEATURES CHANGES IN VERSION 2.4.0CHANGES IN VERSION 2.3.1NEW FEATURES 2.0.0:
1.4.0:
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About: Improved Predictors Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.613011
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About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition. Changes:JProGraM 13.2 -- CHANGE LOG Release date: February 13, 2012 New features: -- Support for Fiedler random graphs/random field models for large-scale networks (ninofreno.graph.fiedler package); -- Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).
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About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction. Changes:Initial Announcement on mloss.org.
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About: Open Source Machine Learning Server Changes:
See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801
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About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks. Changes:The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:
The API and ABI have undergone significant changes, many of which are due to the transition to C++11.
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About: A Tool for Measuring String Similarity Changes:This release fixes the incorrect implementation of the bag distance.
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About: The CAM R-Java software provides a noval way to solve blind source separation problem. Changes:In this version, we fix the problem of not working under newest R version R-3.0.
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About: Nowadays this is very popular to use the deep architectures in machine learning. Deep Belief Networks (DBNs) are deep architectures that use a stack of Restricted Boltzmann Machines (RBM) to create a powerful generative model using training data. DBNs have many abilities such as feature extraction and classification that are used in many applications including image processing, speech processing, text categorization, etc. This paper introduces a new object oriented toolbox with the most important abilities needed for the implementation of DBNs. According to the results of the experiments conducted on the MNIST (image), ISOLET (speech), and the 20 Newsgroups (text) datasets, it was shown that the toolbox can learn automatically a good representation of the input from unlabeled data with better discrimination between different classes. Also on all the aforementioned datasets, the obtained classification errors are comparable to those of the state of the art classifiers. In addition, the toolbox supports different sampling methods (e.g. Gibbs, CD, PCD and our new FEPCD method), different sparsity methods (quadratic, rate distortion and our new normal method), different RBM types (generative and discriminative), GPU based, etc. The toolbox is a user-friendly open source software in MATLAB and Octave and is freely available on the website. Changes:New in toolbox
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About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability. Changes:This is a major release, with several novelties, improvements and fixes, among which:
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About: Toolbox for circular statistics with Matlab (The Mathworks). Changes:Some bugfixes.
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About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode). Changes:LOTS of stuff: https://github.com/BVLC/caffe/releases/tag/v0.9999
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About: HSSVM is a software for solving multi-class problem using Hyper-sphere Support Vector Machines model, implemented by Java. Changes:
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