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Logo XGBoost v0.3.0

by crowwork - September 2, 2014, 02:43:31 CET [ Project Homepage BibTeX Download ] 2286 views, 394 downloads, 2 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.

Changes:

New features: - R support that is now on CRAN

  • Faster tree construction module

  • Support for boosting from initial predictions

  • Linear booster is now parallelized, using parallel coordinated descent.


Logo Cubist 2.07

by zenog - September 2, 2011, 14:52:17 CET [ Project Homepage BibTeX Download ] 2266 views, 592 downloads, 1 subscription

About: Cubist is the regression counterpart to the C5.0 decision tree tool.

Changes:

Initial Announcement on mloss.org.


Logo Linear SVM with general regularization 1.0

by rflamary - October 5, 2012, 15:34:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2262 views, 659 downloads, 1 subscription

About: This package is an implementation of a linear svm solver with a wide class of regularizations on the svm weight vector (l1, l2, mixed norm l1-lq, adaptive lasso). We provide solvers for the classical single task svm problem and for multi-task with joint feature selection or similarity promoting term.

Changes:

Initial Announcement on mloss.org.


Logo Uncorrelated Multilinear Principal Component Analysis 1.0

by hplu - June 18, 2012, 17:23:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2216 views, 442 downloads, 1 subscription

About: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensor-to-vector projection

Changes:

Initial Announcement on mloss.org.


Logo treelearn 1

by iskander - September 21, 2011, 16:12:27 CET [ Project Homepage BibTeX Download ] 2208 views, 525 downloads, 1 subscription

About: A python implementation of Breiman's Random Forests.

Changes:

Initial Announcement on mloss.org.


Logo GritBot 2.01

by zenog - September 2, 2011, 14:56:26 CET [ Project Homepage BibTeX Download ] 2188 views, 540 downloads, 1 subscription

About: GritBot is an data cleaning and outlier/anomaly detection program.

Changes:

Initial Announcement on mloss.org.


Logo hapFabia 1.4.2

by hochreit - December 28, 2013, 17:24:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2183 views, 442 downloads, 1 subscription

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. It detects 100 times smaller segments than previous methods.

Changes:

o citation update

o plot function improved


Logo Graphical Models and Conditional Random Fields Toolbox 2

by jdomke - January 5, 2012, 15:38:20 CET [ Project Homepage BibTeX Download ] 2183 views, 521 downloads, 1 subscription

About: This is a Matlab/C++ "toolbox" of code for learning and inference with graphical models. It is focused on parameter learning using marginalization in the high-treewidth setting.

Changes:

Initial Announcement on mloss.org.


Logo MLPlot Beta

by pascal - August 22, 2011, 11:07:53 CET [ Project Homepage BibTeX Download ] 2182 views, 440 downloads, 1 subscription

About: MLPlot is a lightweight plotting library written in Java.

Changes:

Initial Announcement on mloss.org.


Logo Naive Bayes EM Algorithm 1.0.0

by openpr_nlpr - December 2, 2011, 05:35:09 CET [ Project Homepage BibTeX Download ] 2177 views, 485 downloads, 1 subscription

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.


Showing Items 391-400 of 537 on page 40 of 54: First Previous 35 36 37 38 39 40 41 42 43 44 45 Next Last