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Logo boostree 0.1

by xavierc - December 1, 2007, 03:16:14 CET [ BibTeX Download ] 3909 views, 1355 downloads, 0 comments, 0 subscriptions

About: This package provides an implementation Schapire and Singer's AdaBoost.MH for multi-label classification. As a main feature, the package provides decision-tree weak learning, a generalization of [...]

Changes:

Initial Announcement on mloss.org.


Logo Multilinear Principal Component Analysis 1.3

by hplu - September 8, 2013, 13:04:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3900 views, 741 downloads, 1 subscription

About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data with sample code on gait recognition

Changes:
  1. The MPCA paper is updated with a typo (the MAD measure in Table II) corrected.

  2. Tensor toolbox version 2.1 is included for convenience.

  3. Full code on gait recognition is included for verification and comparison.


Logo FWTN 1.0

by hn - March 25, 2010, 16:58:24 CET [ Project Homepage BibTeX Download ] 3887 views, 857 downloads, 1 subscription

About: Orthonormal wavelet transform for D dimensional tensors in L levels. Generic quadrature mirror filters and tensor sizes. Runtime is O(n), plain C, MEX-wrapper and demo provided.

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Initial Announcement on mloss.org.


Logo redsvd 0.1.0

by hillbig - August 30, 2010, 18:13:55 CET [ Project Homepage BibTeX Download ] 3876 views, 832 downloads, 1 subscription

About: redsvd is a library for solving several matrix decomposition (SVD, PCA, eigen value decomposition) redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 10M nonzero entries in about two second.

Changes:

Initial Announcement on mloss.org.


Logo OLaRankExact 1.0

by antojne - June 24, 2009, 17:03:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3843 views, 924 downloads, 1 subscription

About: OLaRank is an online solver of the dual formulation of support vector machines for sequence labeling using viterbi decoding.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-boost 1.0-0

by r-cran-robot - December 9, 2004, 22:57:00 CET [ Project Homepage BibTeX Download ] 3827 views, 1020 downloads, 1 subscription

About: Boosting Methods for Real and Simulated Data

Changes:

Fetched by r-cran-robot on 2009-06-24 07:16:09.478727


Logo r-cran-caretNWS 0.25

by r-cran-robot - December 3, 2008, 00:00:00 CET [ Project Homepage BibTeX Download ] 3806 views, 882 downloads, 1 subscription

About: Classification and Regression Training in Parallel Using NetworkSpaces: Augment some caret functions using parallel processing

Changes:

Initial Announcement on mloss.org.


Logo mldata.org svn-r1070-Apr-2011

by sonne - April 8, 2011, 10:15:49 CET [ Project Homepage BibTeX Download ] 3788 views, 708 downloads, 1 subscription

About: The source code of the mldata.org site - a community portal for machine learning data sets.

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Initial Announcement on mloss.org.


Logo Tuwo 1.0

by nowozin - May 19, 2009, 09:19:41 CET [ Project Homepage BibTeX Download ] 3787 views, 914 downloads, 1 subscription

About: C++ Library for High-level Computer Vision Tasks

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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 ] 3748 views, 930 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.


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