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About: The High Dimensional Discriminant Analysis (HDDA) toolbox contains an efficient supervised classifier for high-dimensional data. This classifier is based on Gaussian models adapted for [...] Changes:Initial Announcement on mloss.org.
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About: OLaRankGreedy is an online solver of the dual formulation of support vector machines for sequence labeling using greedy inference. Changes:Initial Announcement on mloss.org.
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About: Preparing Changes:Initial Announcement on mloss.org.
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About: The Computational Infrastructure for Operations Research (COIN-OR) project is an initiative to spur the development of open-source software for the operations research community. Changes:Initial Announcement on mloss.org.
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About: Fast Runtime-Flexible Multi-dimensional Arrays and Views for C++ Changes:Initial Announcement on mloss.org.
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About: A fast implementation of several stochastic gradient descent learners for classification, ranking, and ROC area optimization, suitable for large, sparse data sets. Includes Pegasos SVM, SGD-SVM, Passive-Aggressive Perceptron, Perceptron with Margins, Logistic Regression, and ROMMA. Commandline utility and API libraries are provided. Changes:Initial Announcement on mloss.org.
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About: A toolkit for hyperparameter optimization for machine learning algorithms. Changes:Initial Announcement on mloss.org.
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About: A python implementation of Breiman's Random Forests. Changes:Initial Announcement on mloss.org.
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About: OXlearn is a free neural network simulation software that enables you to build, train, test and analyse connectionist neural network models. Because OXlearn is implemented as a Matlab toolbox you can run it on all operation systems (Windows, Linux, MAC, etc.), and there is a compiled version for XP. Changes:Initial Announcement on mloss.org.
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About: ELF provides many well implemented supervised learners for classification and regression tasks with an opportunity of ensemble learning. Changes:Initial Announcement on mloss.org.
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About: stroll (STRuctured Output Learning Library) is a library for Structured Output Learning. Changes:Initial Announcement on mloss.org.
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About: Fast C++ implementation of the variation of information (Meila 2003) and Rand index (Rand 1971) with MATLAB mex files Changes:Initial Announcement on mloss.org.
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About: This database include 164 satellite iamges of different airports from google-earth, the first 110 images are used as training images, include 2337 aircrafts, the remained 54 images are used as test images, include 2206 aircrafts, each aircraft are labeled by two points and one number, indicating the positions of head and tail,and which point is the head. The labeled informations are recorded in two files: train.txt and test.txt, matlab is recommanded to be used for reading these data by import data tool. Changes:Initial Announcement on mloss.org.
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About: This is a large scale online learning implementation with several useful features. See the webpage for more details. Changes:Initial Announcement on mloss.org.
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About: A C++ Library for Discrete Graphical Models Changes:Initial Announcement on mloss.org.
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About: Lightweight CPU/GPU Matrix/Tensor Template Library in C++/CUDA. Support element-wise expression expand in high performance. Code once, run smoothly on both GPU and CPU Changes:Initial Announcement on mloss.org.
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About: MLlib provides a distributed machine learning (ML) library to address the growing need for scalable ML. MLlib is developed in Spark (http://spark.incubator.apache.org/), a cluster computing system designed for iterative computation. Moreover, it is a component of a larger system called MLbase (www.mlbase.org) that aims to provide user-friendly distributed ML functionality both for ML researchers and domain experts. MLlib currently consists of scalable implementations of algorithms for classification, regression, collaborative filtering and clustering. Changes:Initial Announcement on mloss.org.
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About: Feature Selection SVM using penalty functions Changes:Fetched by r-cran-robot on 2013-04-01 00:00:07.509844
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About: A descriptive and programming language independent format and API for the simplified configuration, documentation, and design of computer experiments. Changes:Initial Announcement on mloss.org.
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About: Source code for EM approximate learning in the Latent Topic Hypertext Model. Changes:Initial Announcement on mloss.org.
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