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Logo SVMlin 1.0

by vikas - November 27, 2007, 08:04:48 CET [ Project Homepage BibTeX Download ] 7617 views, 1721 downloads, 1 subscription

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About: SVMlin: Fast Linear SVMs for Supervised and Semi-supervised Learning

Changes:

Initial Announcement on mloss.org.


Logo svmPRAT 1.0

by rangwala - December 28, 2009, 00:27:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6475 views, 1605 downloads, 1 subscription

About: BACKGROUND:Over the last decade several prediction methods have been developed for determining the structural and functional properties of individual protein residues using sequence and sequence-derived information. Most of these methods are based on support vector machines as they provide accurate and generalizable prediction models. RESULTS:We present a general purpose protein residue annotation toolkit (svmPRAT) to allow biologists to formulate residue-wise prediction problems. svmPRAT formulates the annotation problem as a classification or regression problem using support vector machines. One of the key features of svmPRAT is its ease of use in incorporating any user-provided information in the form of feature matrices. For every residue svmPRAT captures local information around the reside to create fixed length feature vectors. svmPRAT implements accurate and fast kernel functions, and also introduces a flexible window-based encoding scheme that accurately captures signals and pattern for training eective predictive models. CONCLUSIONS:In this work we evaluate svmPRAT on several classification and regression problems including disorder prediction, residue-wise contact order estimation, DNA-binding site prediction, and local structure alphabet prediction. svmPRAT has also been used for the development of state-of-the-art transmembrane helix prediction method called TOPTMH, and secondary structure prediction method called YASSPP. This toolkit developed provides practitioners an efficient and easy-to-use tool for a wide variety of annotation problems. Availability: http://www.cs.gmu.edu/~mlbio/svmprat/

Changes:

Initial Announcement on mloss.org.


Logo SVMStructMATLAB 1.2

by andreavedaldi - September 12, 2012, 00:25:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14563 views, 2518 downloads, 1 subscription

About: svm-struct-matlab is a MATLAB wrapper of T. Joachims' SVM^struct solver for structured output support vector machines.

Changes:

Adds support for Xcode 4.0 and Mac OS X 10.7 and greater.


Logo SVQP 2

by leonbottou - January 31, 2009, 14:22:04 CET [ Project Homepage BibTeX Download ] 7155 views, 2319 downloads, 0 subscriptions

About: SVQP1 and SVQP2 are QP solvers for training SVM.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Tapkee 1.0

by blackburn - April 10, 2014, 02:45:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 17254 views, 4809 downloads, 1 subscription

About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction.

Changes:

Initial Announcement on mloss.org.


About: TBEEF, a doubly ensemble framework for recommendation and prediction problems.

Changes:

Included the final technical report.


Logo Tekkotsu 4.0

by touretzky - December 5, 2007, 10:28:02 CET [ Project Homepage BibTeX Download ] 6379 views, 1469 downloads, 0 subscriptions

About: Tekkotsu is a high-level framework for robot programming that provides primitives for perception, manipulation, navigation, and control. It supports a variety of robot platforms.

Changes:

Initial Announcement on mloss.org.


Logo Test 1.0

by willyie - August 23, 2013, 23:05:22 CET [ BibTeX Download ] 2058 views, 723 downloads, 1 subscription

About: Test submission. Is MLOSS working?

Changes:

Initial Announcement on mloss.org.


Logo Thalasso v0.2

by rherault - July 22, 2013, 15:33:59 CET [ Project Homepage BibTeX Download ] 2820 views, 797 downloads, 1 subscription

About: Regularization paTH for LASSO problem (thalasso) thalasso solves problems of the following form: minimize 1/2||X*beta-y||^2 + lambda*sum|beta_i|, where X and y are problem data and beta and lambda are variables.

Changes:

Initial Announcement on mloss.org.


Logo The Choquet Kernel 1.00

by AliFall - February 11, 2014, 16:21:15 CET [ BibTeX BibTeX for corresponding Paper Download ] 3056 views, 1007 downloads, 1 subscription

About: The package computes the optimal parameters for the Choquet kernel

Changes:

Initial Announcement on mloss.org.


Showing Items 611-620 of 664 on page 62 of 67: First Previous 57 58 59 60 61 62 63 64 65 66 67 Next