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Logo Isoline Retrieval SVN rev. 7

by Petey - February 21, 2012, 16:56:09 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2409 views, 511 downloads, 1 subscription

About: Software to perform isoline retrieval, retrieve isolines of an atmospheric parameter from a nadir-looking satellite.

Changes:

Added screenshot, keywords


Logo PLEASD 0.1

by heroesneverdie - September 10, 2012, 03:53:26 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2368 views, 549 downloads, 1 subscription

About: PLEASD: A Matlab Toolbox for Structured Learning

Changes:

Initial Announcement on mloss.org.


Logo Naive Bayes Classifier 1.0.0

by openpr_nlpr - December 2, 2011, 05:25:44 CET [ Project Homepage BibTeX Download ] 2344 views, 616 downloads, 1 subscription

About: This program is a 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. The program uses the multinomial event model for representation, the maximum likelihood estimate with a Laplace smoothing technique for learning parameters. A sparse-data structure is defined to represent the feature vector in the program to seek higher computational speed.

Changes:

Initial Announcement on mloss.org.


Logo Efficient Nonnegative Sparse Coding Algorithm 1.0

by openpr_nlpr - January 4, 2012, 09:44:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2325 views, 488 downloads, 1 subscription

About: Nonnegative Sparse Coding, Discriminative Semi-supervised Learning, sparse probability graph

Changes:

Initial Announcement on mloss.org.


Logo MLFlex 02-21-2012-00-12

by srp33 - April 3, 2012, 16:44:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2258 views, 490 downloads, 1 subscription

About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.)

Changes:

Initial Announcement on mloss.org.


Logo r-cran-quantregForest 0.2-3

by r-cran-robot - June 1, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 2257 views, 536 downloads, 0 subscriptions

About: Quantile Regression Forests

Changes:

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


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

Changes:

Updated the included documentation.


Logo PyStruct 0.2

by t3kcit - July 9, 2014, 09:29:23 CET [ Project Homepage BibTeX Download ] 2207 views, 604 downloads, 1 subscription

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the well-known SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-LogicForest 2.0.0

by r-cran-robot - September 20, 2011, 00:00:00 CET [ Project Homepage BibTeX Download ] 2203 views, 497 downloads, 0 subscriptions

About: Logic Forest

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.077571


About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.

Changes:

Initial Announcement on mloss.org.


Showing Items 421-430 of 565 on page 43 of 57: First Previous 38 39 40 41 42 43 44 45 46 47 48 Next Last