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About: DDN learns and visualize differential dependency networks from condition-specific data. Changes:Initial Announcement on mloss.org.
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About: RLScore - regularized least-squares machine learning algorithms package Changes:Initial Announcement on mloss.org.
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About: DynaML is a Scala environment for conducting research and education in Machine Learning. DynaML comes packaged with a powerful library of classes implementing predictive models and a Scala REPL where one can not only build custom models but also play around with data work-flows. Changes:Initial Announcement on mloss.org.
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About: We study the problem of robust feature extraction based on L21 regularized correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that an L21-norm minimization can be justified from the viewpoint of half-quadratic (HQ) optimization, which facilitates convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify L1-norm and L21-norm minimization within a common framework. In algorithmic part, we propose an L21 regularized correntropy algorithm to extract informative features meanwhile to remove outliers from training data. A new alternate minimization algorithm is also developed to optimize the non-convex correntropy objective. In terms of face recognition, we apply the proposed method to obtain an appearance-based model, called Sparse-Fisherfaces. Extensive experiments show that our method can select robust and sparse features, and outperforms several state-of-the-art subspace methods on largescale and open face recognition datasets. Changes:Initial Announcement on mloss.org. |
About: Software to perform isoline retrieval, retrieve isolines of an atmospheric parameter from a nadir-looking satellite. Changes:Added screenshot, keywords
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About: Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets. For the purpose of algorithm speedup, an agglomerative MS clustering method called Agglo-MS was developed, along with its mode-seeking ability and convergence property analysis. The method is built upon an iterative query set compression mechanism which is motivated by the quadratic bounding optimization nature of MS. The whole framework can be efficiently implemented in linear running time complexity. Changes:Initial Announcement on mloss.org.
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About: Effect Displays for Linear, Generalized Linear, and Other Models Changes:Fetched by r-cran-robot on 2018-01-01 00:00:07.810965
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About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient. Changes:Initial Announcement on mloss.org.
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About: A streaming inference and query engine for the Cross-Categorization model of tabular data. Changes:Initial Announcement on mloss.org.
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About: ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories. Changes:Initial Announcement on mloss.org.
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About: Soltion developed by team Turtle Tamers in the ChaLearn Gesture Challenge (http://www.kaggle.com/c/GestureChallenge2) Changes:Initial Announcement on mloss.org.
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About: Estimates statistical significance of association between variables and their principal components (PCs). Changes:Initial Announcement on mloss.org.
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About: This toolbox implements a novel visualization technique called Sectors on Sectors (SonS), and a extended version called Multidimensional Sectors on Sectors (MDSonS), for improving the interpretation of several data mining algorithms. The MDSonS method makes use of Multidimensional Scaling (MDS) to solve the main drawback of the previous method, namely, the lack of representing distances between pairs of clusters. These methods have been applied for visualizing the results of hierarchical clustering, Growing Hierarchical Self-Organizing Maps (GHSOM), classification trees and several manifolds. These methods make possible to extract all the existing relationships among centroids’ attributes at any hierarchy level. Changes:Initial Announcement on mloss.org.
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About: Regression forests, Random Forests for regression. Original implementation by Leo Breiman. Changes:Initial Announcement on mloss.org.
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About: Collection of algorithms for Gaussian Processes. Regression, Classification, Multi task, Multi output, Hierarchical, Sparse Changes:Initial Announcement on mloss.org.
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About: Java package for calculating Entropy for Machine Learning Applications. It has implemented several methods of handling missing values. So it can be used as a lab for examining missing values. Changes:Discretizing numerical values is added to calculate mode of values and fractional replacement of missing ones. class diagram is on the web http://profs.basu.ac.ir/bathaeian/free_space/jemla.rar
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About: This is a class to calculate histogram of LBP (local binary patterns) from an input image, histograms of LBP-TOP (local binary patterns on three orthogonal planes) from an image sequence, histogram of the rotation invariant VLBP (volume local binary patterns) or uniform rotation invariant VLBP from an image sequence. Changes:Initial Announcement on mloss.org.
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About: The original Random Forests implementation by Breiman and Cutler. Changes:Initial Announcement on mloss.org.
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