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About: OpenPR-NBEM is an C++ implementation of Naive Bayes Classifier, which is a well-known generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. OpenPR-NBEM uses the multinomial event model for representation. The maximum likelihood estimate is used for supervised learning, and the expectation-maximization estimate is used for semi-supervised and un-supervised learning. Changes:Initial Announcement on mloss.org.
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About: An annotated java framework for machine learning, aimed at making it really easy to access analytically functions. Changes:Now supports OLS and GLS regression and NaiveBayes classification
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About: Log-linear analysis for high-dimensional data Changes:Initial Announcement on mloss.org.
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About: Jie Gui, Zhenan Sun, Guangqi Hou, Tieniu Tan, "An optimal set of code words and correntropy for rotated least squares regression", International Joint Conference on Biometrics, 2014, pp. 1-6 Changes:Initial Announcement on mloss.org.
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About: A fast and robust learning of Bayesian networks Changes:Initial Announcement on mloss.org.
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About: Classification and Regression Training in Parallel Using NetworkSpaces: Augment some caret functions using parallel processing Changes:Initial Announcement on mloss.org.
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About: revised version of BACOM Changes:Initial Announcement on mloss.org.
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About: The software provides an implementation of a filter/smoother based on Gibbs sampling, which can be used for inference in dynamical systems. Changes:Initial Announcement on mloss.org.
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About: The pboost toolbox is a set of command line programs and a Matlab wrapper for mining frequent subsequences and sequence classification. For our purposes, a sequence is defined an ordered sequence of [...] Changes:Initial Announcement on mloss.org.
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About: Jatecs is an open source Java library focused on automatic text categorization. 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: Approximate Rank One FACtorization of tensors. An algorithm for factorization of three-way-tensors and determination of their rank, includes example applications. Changes:Initial Announcement on mloss.org.
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About: Nonnegative Sparse Coding, Discriminative Semi-supervised Learning, sparse probability graph Changes:Initial Announcement on mloss.org.
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About: An open-source Python toolbox to analyze mobile phone metadata. Changes:Initial Announcement on mloss.org.
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About: Pynopticon is a toolbox that allows you to create and train your own object recognition classifiers. It makes rapid prototyping of object recognition work flows a snap. Simply create a dataset of [...] Changes:Initial Announcement on mloss.org.
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About: This algorithm is described in Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval. See https://github.com/zhaofang0627/cuda-convnet-for-hashing 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: A python implementation of Breiman's Random Forests. Changes:Initial Announcement on mloss.org.
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About: This program is a C++ implementation of Naive Bayes Classifier, which is a well-known generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. The program uses the multinomial event model for representation, the maximum likelihood estimate with a Laplace smoothing technique for learning parameters. A sparse-data structure is defined to represent the feature vector in the program to seek higher computational speed. Changes:Initial Announcement on mloss.org.
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