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Logo C5.0 2.07

by zenog - September 2, 2011, 14:49:04 CET [ Project Homepage BibTeX Download ] 3817 views, 1035 downloads, 1 subscription

About: C5.0 is the successor of the C4.5 decision tree algorithm/tool. In particular, it is faster and more memory-efficient.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-bigRR 1.3-10

by r-cran-robot - August 23, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 3812 views, 970 downloads, 0 subscriptions

About: Generalized Ridge Regression (with special advantage for p >> n cases)

Changes:

Fetched by r-cran-robot on 2016-07-01 00:00:03.666242


Logo Graphical Models and Conditional Random Fields Toolbox 2

by jdomke - January 5, 2012, 15:38:20 CET [ Project Homepage BibTeX Download ] 3806 views, 904 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 Gibbs RTSS 1.0

by marc - April 4, 2011, 19:58:43 CET [ BibTeX BibTeX for corresponding Paper Download ] 3803 views, 1039 downloads, 1 subscription

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.


Logo hcluster 0.2.0

by damianeads - December 14, 2008, 14:03:49 CET [ Project Homepage BibTeX Download ] 3785 views, 1001 downloads, 1 subscription

About: This library provides Python functions for agglomerative clustering. Its features include

Changes:

Initial Announcement on mloss.org.


Logo Hub Miner 1.1

by nenadtomasev - January 22, 2015, 16:33:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3780 views, 701 downloads, 2 subscriptions

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:
  • BibTex support for all algorithm implementations, making all of them easy to reference (via algref package).

  • Two more hubness-aware approaches (meta-metric-learning and feature construction)

  • An implementation of Hit-Miss networks for analysis.

  • Several minor bug fixes.

  • The following instance selection methods were added: HMScore, Carving, Iterative Case Filtering, ENRBF.

  • The following clustering quality indexes were added: Folkes-Mallows, Calinski-Harabasz, PBM, G+, Tau, Point-Biserial, Hubert's statistic, McClain-Rao, C-root-k.

  • Some more experimental scripts have been included.

  • Extensions in the estimation of hubness risk.

  • Alias and weighted reservoir methods for weight-proportional random selection.


Logo r-cran-quantregForest 0.2-3

by r-cran-robot - June 1, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 3763 views, 852 downloads, 0 subscriptions

About: Quantile Regression Forests

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.576421


Logo MLlib 0.8

by atalwalkar - October 10, 2013, 00:56:25 CET [ Project Homepage BibTeX Download ] 3730 views, 699 downloads, 1 subscription

About: MLlib provides a distributed machine learning (ML) library to address the growing need for scalable ML. MLlib is developed in Spark (http://spark.incubator.apache.org/), a cluster computing system designed for iterative computation. Moreover, it is a component of a larger system called MLbase (www.mlbase.org) that aims to provide user-friendly distributed ML functionality both for ML researchers and domain experts. MLlib currently consists of scalable implementations of algorithms for classification, regression, collaborative filtering and clustering.

Changes:

Initial Announcement on mloss.org.


Logo VoxForge 0.1

by nshmyrev - February 7, 2010, 02:25:43 CET [ Project Homepage BibTeX Download ] 3695 views, 1182 downloads, 0 comments, 1 subscription

About: Free Speech Database for ASR engines

Changes:

Initial Announcement on mloss.org.


Logo Sparse Compositional Metric Learning v1.1

by bellet - August 16, 2015, 16:41:20 CET [ BibTeX BibTeX for corresponding Paper Download ] 3690 views, 1278 downloads, 2 subscriptions

About: Scalable learning of global, multi-task and local metrics from data

Changes:

Various minor bug fixes and improvements. The basis and triplet generation now fully supports with datasets with very small classes and arbitrary labels (no need to be consecutive or positive). The computational and memory efficiency of the code when data is high dimensional has been largely improved, and we generate a rectangular (smaller) projection matrix when the number of selected basis is smaller than the dimension. K-NN classification with local metrics has been optimized and made significantly less costly in both time and memory.


Showing Items 431-440 of 622 on page 44 of 63: First Previous 39 40 41 42 43 44 45 46 47 48 49 Next Last