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: A Matlab implementation of Sparse PCA using the inverse power method for nonlinear eigenproblems. Changes:
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About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more Changes:This version comes with Distributed and Mobile Examples
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About: Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...] Changes:Apache Mahout introduces a new math environment we call Samsara, for its theme of universal renewal. It reflects a fundamental rethinking of how scalable machine learning algorithms are built and customized. Mahout-Samsara is here to help people create their own math while providing some off-the-shelf algorithm implementations. At its core are general linear algebra and statistical operations along with the data structures to support them. You can use is as a library or customize it in Scala with Mahout-specific extensions that look something like R. Mahout-Samsara comes with an interactive shell that runs distributed operations on a Spark cluster. This make prototyping or task submission much easier and allows users to customize algorithms with a whole new degree of freedom. Mahout Algorithms include many new implementations built for speed on Mahout-Samsara. They run on Spark 1.3+ and some on H2O, which means as much as a 10x speed increase. You’ll find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative filtering. The new spark-itemsimilarity enables the next generation of cooccurrence recommenders that can use entire user click streams and context in making recommendations.
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About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications. Changes:
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About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as cross-validation and a plethora of score functions. Changes:This minor release has the same feature set as Optunity 1.1.0, but incorporates several bug fixes, mostly related to the specification of structured search spaces.
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About: SALSA (Software lab for Advanced machine Learning with Stochastic Algorithms) is an implementation of the well-known stochastic algorithms for Machine Learning developed in the high-level technical computing language Julia. The SALSA software package is designed to address challenges in sparse linear modelling, linear and non-linear Support Vector Machines applied to large data samples with user-centric and user-friendly emphasis. Changes:Initial Announcement on mloss.org.
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About: Presage is an intelligent predictive text entry platform. Changes:Initial Announcement on mloss.org.
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About: libnabo is a fast K Nearset Neighbor library for low-dimensional spaces. Changes:
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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: Data Sets, Functions and Examples from the Book Changes:Fetched by r-cran-robot on 2018-01-01 00:00:07.925283
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About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'. Changes:Moved project to GitHub.
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About: Learning string edit distance / similarity from data Changes:Added datasets used in the experiments of the paper
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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: FAST is an implementation of Hidden Markov Models with Features. It allows features to modify both emissions and transition probabilities. Changes:Initial Announcement on mloss.org.
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About: rabit (Reliable Allreduce and Broadcast Interface) is a light weight library that provides a fault tolerant interface of Allreduce and Broadcast for portable , scalable and reliable distributed machine learning programs. Rabit programs can run on various platforms such as Hadoop, MPI and no installation is needed. Rabit now support kmeans clustering, and distributed xgboost: an extremely efficient disrtibuted boosted tree(GBDT) toolkit. Changes:Initial Announcement on mloss.org.
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About: C++ software for statistical classification, probability estimation and interpolation/non-linear regression using variable bandwidth kernel estimation. Changes:New in Version 0.9.8:
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About: A MATLAB toolbox for defining complex machine learning comparisons Changes:Initial Announcement on mloss.org.
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About: A community detection method based on constrained fractional set programming (CFSP). Changes:Initial Announcement on mloss.org.
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About: Generalized Ridge Regression (with special advantage for p >> n cases) Changes:Fetched by r-cran-robot on 2018-05-01 00:00:05.929954
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