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About: Classification rule based on Bayesian naive Bayes models with feature selection bias corrected Changes:Fetched by r-cran-robot on 2012-12-01 00:00:07.510624
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About: Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data. It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. Changes:Initial Announcement on mloss.org.
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About: The package estimates the matrix of partial correlations based on different regularized regression methods: lasso, adaptive lasso, PLS, and Ridge Regression. Changes:Initial Announcement on mloss.org.
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About: Learns dynamic network changes across conditions and visualize the results in Cytoscape. Changes:Initial Announcement on mloss.org.
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About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data Changes:Initial Upload
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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: A decision tree learner that is designed to be reasonably fast, but the primary goal is ease of use Changes:Initial Announcement on mloss.org.
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About: Denoising images via normalized convolution Changes:Initial Announcement on mloss.org.
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About: A Matlab implementation of Uncorrelated Multilinear Discriminant Analysis (UMLDA) for dimensionality reduction of tensor data via tensor-to-vector projection Changes:Initial Announcement on mloss.org.
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About: Use the power of crowdsourcing to create ensembles. Changes:Initial Announcement on mloss.org.
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About: This software is designed for learning translation invariant kernels for classification with support vector machines. Changes:Initial Announcement on mloss.org.
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About: Rival is an open source Java toolkit for recommender system evaluation. It provides a simple way to create evaluation results comparable across different recommendation frameworks. Changes:Initial Announcement on mloss.org.
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About: Bayesian state-space modelling and inference on high-performance computer hardware. Changes:Initial Announcement on mloss.org.
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About: GritBot is an data cleaning and outlier/anomaly detection program. Changes:Initial Announcement on mloss.org.
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About: Logic Forest Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.077571
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About: BudgetedSVM is an open-source C++ toolbox for scalable non-linear classification. The toolbox can be seen as a missing link between LibLinear and LibSVM, combining the efficiency of linear with the accuracy of kernel SVM. We provide an Application Programming Interface for efficient training and testing of non-linear classifiers, supported by data structures designed for handling data which cannot fit in memory. We also provide command-line and Matlab interfaces, providing users with an efficient, easy-to-use tool for large-scale non-linear classification. Changes:Changed license from LGPL v3 to Modified BSD.
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About: ClowdFlows is a web based platform for service oriented data mining publicly available at http://clowdflows.org . A web based interface allows users to construct data mining workflows that are hosted on the web and can be (if allowed by the author) accessed by anyone by following a URL of the workflow. Changes:Initial Announcement on mloss.org.
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About: The open-source C-package fastICA implements the fastICA algorithm of Aapo Hyvarinen et al. (URL: http://www.cs.helsinki.fi/u/ahyvarin/) to perform Independent Component Analysis (ICA) and Projection Pursuit. fastICA is released under the GNU Public License (GPL). Changes:Initial Announcement on mloss.org.
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About: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensor-to-vector projection Changes:Initial Announcement on mloss.org.
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About: This archive contains a Matlab implementation of the Multilinear Principal Component Analysis (MPCA) algorithm and MPCA+LDA, as described in the paper Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "MPCA: Multilinear Principal Component Analysis of Tensor Objects", IEEE Transactions on Neural Networks, Vol. 19, No. 1, Page: 18-39, January 2008. Changes:Initial Announcement on mloss.org.
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