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Logo Bilingual Text Classification 0.1

by jorcisai - April 9, 2010, 15:13:08 CET [ BibTeX BibTeX for corresponding Paper Download ] 3878 views, 1329 downloads, 1 subscription

About: This software package implements a series of statistical mixture models for bilingual text classificacion trained by the EM algorihtm.

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Logo arts 0.2

by sonne - May 25, 2009, 09:56:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6153 views, 1325 downloads, 1 subscription

About: ARTS is an accurate predictor for Transcription Start Sites (TSS).

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Logo Ohmm 0.02

by hillbig - May 21, 2009, 10:07:53 CET [ Project Homepage BibTeX Download ] 4680 views, 1323 downloads, 1 subscription

About: Ohmm is a library for learning hidden Markov models by using Online EM algorithm. This library is specialized for large scale data; e.g. 1 million words. The output includes parameters, and estimation results.

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Logo Kernel Multiple Logistic Regression 1.0

by mseeger - November 10, 2007, 22:16:50 CET [ Project Homepage BibTeX Download ] 5742 views, 1320 downloads, 0 subscriptions

About: Efficient implementation of penalized multiple logistic regression (aka multi-class) with Mercer kernels, aka MAP approximation to the multi-class Gaussian process model. This includes [...]

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About: A Java library to create, process and manage mixtures of exponential families.

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Logo svmPRAT 1.0

by rangwala - December 28, 2009, 00:27:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5256 views, 1313 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/

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Logo chestnut Machine Learning Suite 0.1.1

by damianeads - October 7, 2008, 13:04:19 CET [ Project Homepage BibTeX Download ] 5445 views, 1306 downloads, 1 subscription

About: The Chestnut Machine Learning Library is a suite of machine learning algorithms written in Python with some code written in C for efficiency. Most algorithms are called with a simple, functional API [...]

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Logo Experiment Databases for Machine Learning 0.1

by JoaquinVanschoren - October 7, 2008, 18:06:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7769 views, 1305 downloads, 1 subscription

About: Experiment Databases for Machine Learning is a large public database of machine learning experiments as well as a framework for producing similar databases for specific goals. It provides a way to [...]

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About: This page contains the implementation used in the paper „Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models“ by Florian Steinke, Matthias [...]

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Logo GPUML GPUs for kernel machines 4

by balajivasan - February 26, 2010, 18:12:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6868 views, 1289 downloads, 1 subscription

About: GPUML is a library that provides a C/C++ and MATLAB interface for speeding up the computation of the weighted kernel summation and kernel matrix construction on GPU. These computations occur commonly in several machine learning algorithms like kernel density estimation, kernel regression, kernel PCA, etc.

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Initial Announcement on mloss.org.


Showing Items 321-330 of 622 on page 33 of 63: First Previous 28 29 30 31 32 33 34 35 36 37 38 Next Last