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Showing Items 101-120 of 674 on page 6 of 34: Previous 1 2 3 4 5 6 7 8 9 10 11 Next Last

Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24796 views, 4533 downloads, 0 subscriptions

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About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Logo MATLAB spectral clustering package 1.1

by wenyenc - February 4, 2010, 01:54:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24867 views, 4531 downloads, 0 subscriptions

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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:
  • Add bib
  • Add code of nystrom without orthogonalization
  • Add accuracy quality measure
  • Add more running scripts

Logo r-cran-GAMBoost 1.2-2

by r-cran-robot - April 1, 2013, 00:00:04 CET [ Project Homepage BibTeX Download ] 23013 views, 4526 downloads, 0 subscriptions

About: Generalized linear and additive models by likelihood based boosting

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:04.893311


Logo The Infinite Hidden Markov Model 0.5

by jvangael - July 21, 2010, 23:41:24 CET [ BibTeX BibTeX for corresponding Paper Download ] 26787 views, 4470 downloads, 0 subscriptions

About: An implementation of the infinite hidden Markov model.

Changes:

Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.


Logo libAGF 0.9.8

by Petey - December 6, 2014, 02:35:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 23903 views, 4389 downloads, 0 subscriptions

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:

  • bug fixes: svm file conversion works properly and is more general

  • non-hierarchical multi-borders has 3 options for solving for the conditional probabilities: matrix inversion, voting, and matrix inversion over-ridden by voting, with re-normalization

  • multi-borders now works with external binary classifiers

  • random numbers resolve a tie when selecting classes based on probabilities

  • pair of routines, sort_discrete_vectors and search_discrete_vectors, for classification based on n-d binning (still experimental)

  • command options have been changed with many new additions, see QUICKSTART file or run the relevant commands for details


Logo JMLR arules Mining Association Rules and Frequent Itemsets 1.0-6

by mhahsler - February 3, 2012, 10:49:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14529 views, 4369 downloads, 0 subscriptions

About: Infrastructure for representing, manipulating and analyzing transaction data and frequent patterns.

Changes:

Initial Announcement on mloss.org.


Logo FABIA 2.8.0

by hochreit - October 18, 2013, 10:14:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21223 views, 4354 downloads, 0 subscriptions

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About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing.

Changes:

CHANGES IN VERSION 2.8.0

NEW FEATURES

o rescaling of lapla
o extractPlot does not plot sorted matrices

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

  • spfabia: fabia for a sparse data matrix (in sparse matrix format) and sparse vector/matrix computations in the code to speed up computations. spfabia applications: (a) detecting >identity by descent< in next generation sequencing data with rare variants, (b) detecting >shared haplotypes< in disease studies based on next generation sequencing data with rare variants;
  • fabia for non-negative factorization (parameter: non_negative);
  • changed to C and removed dependencies to Rcpp;
  • improved update for lambda (alpha should be smaller, e.g. 0.03);
  • introduced maximal number of row elements (lL);
  • introduced cycle bL when upper bounds nL or lL are effective;
  • reduced computational complexity;
  • bug fixes: (a) update formula for lambda: tighter approximation, (b) corrected inverse of the conditional covariance matrix of z;

1.4.0:

  • New option nL: maximal number of biclusters per row element;
  • Sort biclusters according to information content;
  • Improved and extended preprocessing;
  • Update to R2.13

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 23415 views, 4310 downloads, 0 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

Changes:
  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version


Logo Salad 0.6.1

by chwress - June 17, 2016, 11:26:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 23002 views, 4299 downloads, 0 subscriptions

About: A Content Anomaly Detector based on n-Grams

Changes:

A teeny tiny fix to correctly handle input strings shorter than a registers width


Logo PredictionIO 0.7.0

by simonc - April 29, 2014, 20:59:57 CET [ Project Homepage BibTeX Download ] 20114 views, 4295 downloads, 0 subscriptions

About: Open Source Machine Learning Server

Changes:
  • Single machine version for small-to-medium scale deployments
  • Integrated GraphChi (disk-based large-scale graph computation) and algorithms: ALS, CCD++, SGD, CLiMF
  • Improved runtime for training and offline evaluation
  • Bug fixes

See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801


Logo libnabo 1.0.6

by smagnenat - August 5, 2015, 12:16:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21337 views, 4171 downloads, 0 subscriptions

About: libnabo is a fast K Nearset Neighbor library for low-dimensional spaces.

Changes:
  • Reset point indices of results with distances exceeding threshold (#23, #24)
  • Fine tune the find_package() capability and add uninstall target (#22)
  • Fixed compiler warning (#18)
  • Added OpenMP support (#20, #21)
  • Build type tuning (#19)
  • Fix: terminal comma in enum requires C++11
  • Fix UBSAN error calculating maxNodeCount (#16, #17)
  • Fixed tiny (yet significant) error in the Python doc strings (#15)
  • Compile static lib with PIC (#14)
  • Added configure scripts for full catkinization
  • Catkinization of libnabo (following REP136)
  • Update README.md Added Simon as the maintainer.
  • [test] use CLOCK_PROF for NetBSD build
  • Fixed CppCheck warning. Fix broken install when doxygen is not found
  • Fix cmake stylistic issue
  • Make python install respect custom CMAKE_INSTALL_PREFIX
  • Fix broken install when doxygen is not found

Logo SimpleMKL 0.5

by arakotom - June 11, 2008, 00:56:47 CET [ Project Homepage BibTeX Download ] 16329 views, 4162 downloads, 0 subscriptions

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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox

Changes:

Initial Announcement on mloss.org.


Logo JProGraM 13.2

by ninofreno - February 13, 2013, 20:29:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21708 views, 4152 downloads, 0 subscriptions

About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.

Changes:

JProGraM 13.2 -- CHANGE LOG

Release date: February 13, 2012

New features: -- Support for Fiedler random graphs/random field models for large-scale networks (ninofreno.graph.fiedler package); -- Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).


Logo r-cran-VR 7.2-49

by r-cran-robot - September 25, 2009, 00:00:00 CET [ Project Homepage BibTeX Download ] 16901 views, 4103 downloads, 0 subscriptions

About: VR

Changes:

Fetched by r-cran-robot on 2009-10-03 07:16:05.643423


Logo DAL 1.1

by ryota - February 18, 2014, 19:07:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24907 views, 4092 downloads, 0 subscriptions

About: DAL is an efficient and flexibible MATLAB toolbox for sparse/low-rank learning/reconstruction based on the dual augmented Lagrangian method.

Changes:
  • Supports weighted lasso (dalsqal1.m, dallral1.m)
  • Supports weighted squared loss (dalwl1.m)
  • Bug fixes (group lasso and elastic-net-regularized logistic regression)

Logo Harry 0.4.2

by konrad - April 16, 2016, 10:50:38 CET [ Project Homepage BibTeX Download ] 19080 views, 4083 downloads, 0 subscriptions

About: A Tool for Measuring String Similarity

Changes:

This release fixes the incorrect implementation of the bag distance.


Logo nimfa A Python Library for Nonnegative Matrix Factorization 1.0

by marinkaz - March 22, 2012, 02:38:18 CET [ Project Homepage BibTeX Download ] 8487 views, 4072 downloads, 0 subscriptions

About: Nimfa is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring. Both dense and sparse matrix representation are supported.

Changes:

Initial Announcement on mloss.org.


Logo RapidMiner 4.0

by ingomierswa - November 16, 2007, 02:31:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 23622 views, 4071 downloads, 0 comments, 0 subscriptions

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About: RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...]

Changes:

Initial Announcement on mloss.org.


Logo JMLR Java Machine Learning Library 0.1.5

by thomas - August 20, 2009, 23:47:45 CET [ Project Homepage BibTeX Download ] 30274 views, 3947 downloads, 0 subscriptions

About: Java-ML is a collection of machine learning and data mining algorithms, which aims to be a readily usable and easily extensible API for both software developers and research scientists.

Changes:

new release


Logo DeeBNet, a new object oriented MATLAB toolbox for Deep Belief Networks 3.2

by keyvanrad - June 26, 2016, 16:19:55 CET [ Project Homepage BibTeX Download ] 18445 views, 3883 downloads, 0 subscriptions

About: Nowadays this is very popular to use the deep architectures in machine learning. Deep Belief Networks (DBNs) are deep architectures that use a stack of Restricted Boltzmann Machines (RBM) to create a powerful generative model using training data. DBNs have many abilities such as feature extraction and classification that are used in many applications including image processing, speech processing, text categorization, etc. This paper introduces a new object oriented toolbox with the most important abilities needed for the implementation of DBNs. According to the results of the experiments conducted on the MNIST (image), ISOLET (speech), and the 20 Newsgroups (text) datasets, it was shown that the toolbox can learn automatically a good representation of the input from unlabeled data with better discrimination between different classes. Also on all the aforementioned datasets, the obtained classification errors are comparable to those of the state of the art classifiers. In addition, the toolbox supports different sampling methods (e.g. Gibbs, CD, PCD and our new FEPCD method), different sparsity methods (quadratic, rate distortion and our new normal method), different RBM types (generative and discriminative), GPU based, etc. The toolbox is a user-friendly open source software in MATLAB and Octave and is freely available on the website.

Changes:

New in toolbox

  • Using GPU in Backpropagation
  • Revision of some demo scripts
  • Function approximation with multiple outputs
  • Feature extraction with GRBM in first layer

cardinal


Showing Items 101-120 of 674 on page 6 of 34: Previous 1 2 3 4 5 6 7 8 9 10 11 Next Last