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Logo C5.0 2.07

by zenog - September 2, 2011, 14:49:04 CET [ Project Homepage BibTeX Download ] 3818 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-GMMBoost 1.0.3

by r-cran-robot - September 27, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 4977 views, 1029 downloads, 0 subscriptions

About: Likelihood-based Boosting for Generalized mixed models

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.366545


About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification.

Changes:

Initial Announcement on mloss.org.


Logo hcluster 0.2.0

by damianeads - December 14, 2008, 14:03:49 CET [ Project Homepage BibTeX Download ] 3786 views, 1001 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo Cubist 2.07

by zenog - September 2, 2011, 14:52:17 CET [ Project Homepage BibTeX Download ] 3610 views, 993 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo Epistatic MAP Imputation 1.1

by colm - November 25, 2010, 21:01:10 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4215 views, 986 downloads, 1 subscription

About: Epistatic miniarray profiles (E-MAPs) are a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. This project contains nearest neighbor based tools for the imputation and prediction of these missing values. The code is implemented in Python and uses a nearest neighbor based approach. Two variants are used - a simple weighted nearest neighbors, and a local least squares based regression.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-rminer 1.3

by r-cran-robot - October 9, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 4629 views, 981 downloads, 0 subscriptions

About: Simpler use of data mining methods (e.g. NN and SVM) in classification and regression.

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:08.226306


Logo Action Recognition by Dense Trajectories 1.0

by openpr_nlpr - June 6, 2012, 11:38:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5472 views, 978 downloads, 1 subscription

About: The code is for computing state-of-the-art video descriptors for action recognition. The most up-to-date information can be found at: http://lear.inrialpes.fr/people/wang/dense_trajectories

Changes:

Initial Announcement on mloss.org.


Logo QuickDT 0.1

by sanity - September 21, 2011, 13:43:37 CET [ Project Homepage BibTeX Download ] 3610 views, 977 downloads, 1 subscription

About: A decision tree learner that is designed to be reasonably fast, but the primary goal is ease of use

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 ] 3818 views, 973 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


Showing Items 411-420 of 622 on page 42 of 63: First Previous 37 38 39 40 41 42 43 44 45 46 47 Next Last