RSS Feed - Blog
About: Hivemall is a scalable machine learning library running on Hive/Hadoop. Changes:
|
About: Generalized linear and additive models by likelihood based boosting Changes:Fetched by r-cran-robot on 2013-04-01 00:00:04.893311
|
About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.
|
About: Toolbox for circular statistics with Matlab (The Mathworks). Changes:Some bugfixes.
|
About: A Java Toolbox for Scalable Probabilistic Machine Learning. Changes:
Detailed information can be found in the toolbox's web page
|
About: Generalised Stirling Numbers for Pitman-Yor Processes: this library provides ways of computing generalised 2nd-order Stirling numbers for Pitman-Yor and Dirichlet processes. Included is a tester and parameter optimiser. This accompanies Buntine and Hutter's article: http://arxiv.org/abs/1007.0296, and a series of papers by Buntine and students at NICTA and ANU. Changes:Moved repository to GitHub, and added thread support to use the main table lookups in multi-threaded code.
|
About: A MATLAB spectral clustering package to deal with large data sets. Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been [...] Changes:
|
About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning. Changes:Changelog pyGPs v1.3.2December 15th 2014
|
About: Lua-MapReduce framework implemented in Lua using luamongo driver and MongoDB as storage. It follows Iterative MapReduce for training of Machine Learning statistical models. Changes:
|
About: KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages. At the moment, KReator supports Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), Relational Bayesian Networks (RBN), and Probabilistic Prolog (ProbLog). Changes:
|
About: Bayesian Additive Regression Trees Changes:Fetched by r-cran-robot on 2018-09-01 00:00:04.269138
|
About: Logic Regression Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.139495
|
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.
|
About: Regularization for semiparametric additive hazards regression Changes:Fetched by r-cran-robot on 2018-09-01 00:00:03.378832
|
About: LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, L1-loss linear SVM, and multi-class SVM Changes:Initial Announcement on mloss.org.
|
About: A header-only C++ library for solving large scale eigenvalue problems Changes:
|
About: HSSVM is a software for solving multi-class problem using Hyper-sphere Support Vector Machines model, implemented by Java. Changes:
|
About: R package facilitating the simulation and evaluation of context-free and contextual Multi-Armed Bandit policies. Changes:Minor update.
|
About: MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to [...] Changes:MALLET 2.0 RC4 Release Notes July 16, 2009 Major updates: An implementation of generalized expectation criteria training of MaxEnt classifiers and methods for obtaining constraints (c.f. Gregory Druck, Gideon Mann, Andrew McCallum "Learning from Labeled Features using Generalized Expectation Criteria.") PagedInstanceList has been substantially rewritten by Mike Bond. Bug fixes to topic model hyperparameter optimization and topic inference.
|
About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier. Changes:
|
