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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.
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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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About: The goal of the project is to provide a programming environment for easily exploring advanced topics in artificial intelligence and robotics without having to worry about the low-level details of [...] Changes:Initial Announcement on mloss.org.
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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 [...] Changes:Initial Announcement on mloss.org.
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About: The incomplete Cholesky decomposition for a dense symmetric positive definite matrix A is a simple way of approximating A by a matrix of low rank (you can choose the rank). It has been used [...] Changes:Initial Announcement on mloss.org.
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About: This package implements Ideal PCA in MATLAB. Ideal PCA is a (cross-)kernel based feature extraction algorithm which is (a) a faster alternative to kernel PCA and (b) a method to learn data manifold certifying features. Changes:Initial Announcement on mloss.org.
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About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification. Changes:Initial Announcement on mloss.org.
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About: Elastic-Net for Sparse Estimation and Sparse PCA Changes:Fetched by r-cran-robot on 2013-04-01 00:00:04.831694
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About: A Java library to create, process and manage mixtures of exponential families. Changes:Initial Announcement on mloss.org.
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About: In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp, these images and databases are included in this file, except munich database. Changes:Initial Announcement on mloss.org.
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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. Changes:Initial Announcement on mloss.org.
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About: Given many points in ROC (Receiver Operator Characteristics) space, computes the convex hull. Changes:Initial Announcement on mloss.org.
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About: SeDuMi is a software package to solve optimization problems over symmetric cones. This includes linear, quadratic, second order conic and semidefinite optimization, and any combination of these. Changes:Initial Announcement on mloss.org.
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About: You should never compute, maintain, or update the inverse of a symmetric positive definite matrix if you do not have to. Computing the inverse or manipulating it is inherently instable. You can [...] Changes:Initial Announcement on mloss.org.
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About: An annotated java framework for machine learning, aimed at making it really easy to access analytically functions. Changes:Now supports OLS and GLS regression and NaiveBayes classification
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About: The source code of the mldata.org site - a community portal for machine learning data sets. Changes:Initial Announcement on mloss.org.
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About: This is a set of MATLAB(R) functions and MEX files which I wrote to make working with this system somewhat bearable. They allow to call BLAS and LAPACK functions, which do very efficient dense [...] Changes:Initial Announcement on mloss.org.
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About: NetKit is an open-source Network Learning toolkit for statistical relational learning. Its architecture is extremely modular, making it easy to combine different learning algorithms. Changes:Initial Announcement on mloss.org.
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