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About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects. 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: AIDE (Automata Identification Engine) is a free open source tool for automata inference algorithms developed in C# .Net. Changes:Initial Announcement on mloss.org.
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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: KEEL (Knowledge Extraction based on Evolutionary Learning) is an open source (GPLv3) Java software tool that can be used for a large number of different knowledge data discovery tasks. KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms. It contains a wide variety of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, among others), computational intelligence based learning algorithms, hybrid models, statistical methodologies for contrasting experiments and so forth. It allows to perform a complete analysis of new computational intelligence proposals in comparison to existing ones. Moreover, KEEL has been designed with a two-fold goal: research and educational. KEEL is also coupled with KEEL-dataset: a webpage that aims at providing to the machine learning researchers a set of benchmarks to analyze the behavior of the learning methods. Concretely, it is possible to find benchmarks already formatted in KEEL format for classification (such as standard, multi instance or imbalanced data), semi-supervised classification, regression, time series and unsupervised learning. Also, a set of low quality data benchmarks is maintained in the repository. Changes:Initial Announcement on mloss.org.
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About: A Deep Learning API and server 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: Regression forests, Random Forests for regression. Original implementation by Leo Breiman. Changes:Initial Announcement on mloss.org.
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About: ReFr is a software architecture for specifying, training and using reranking models. Changes:Initial Announcement on mloss.org.
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About: Learning M-Way Tree - Web Scale Clustering - EM-tree, K-tree, k-means, TSVQ, repeated k-means, clustering, random projections, random indexing, hashing, bit signatures Changes:Initial Announcement on mloss.org.
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About: streamDM is a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of data streams. Changes:Initial Announcement on mloss.org.
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About: Block-Coordinate Frank-Wolfe Optimization for Structural SVMs 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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About: The implementation of adaptive probabilistic mappings. Changes:Initial Announcement on mloss.org.
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About: a parallel LDA learning toolbox in Multi-Core Systems for big topic modeling. Changes:Initial Announcement on mloss.org.
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About: FsAlg is a linear algebra library that supports generic types. Changes:Initial Announcement on mloss.org.
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About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods. Changes:Initial Announcement on mloss.org.
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About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms. Changes:Initial Announcement on mloss.org.
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About: CURFIL uses NVIDIA CUDA to accelerate random forest training and prediction for RGB and RGB-D images. It focuses on image labelling tasks, such as image segmentation or classification applications. CURFIL allows to search for optimal hyper-parameter configurations (e.g. using the hyperopt) package) by massively decreasing training time. Changes:Initial Announcement on mloss.org.
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About: Software for graph similarity search for massive graph databases Changes:Initial Announcement on mloss.org.
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