Showing Items 481490 of 674 on page 49 of 68: First Previous 44 45 46 47 48 49 50 51 52 53 54 Next Last
About: Epistatic miniarray profiles (EMAPs) are a highthroughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from EMAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values  up to 35%  that can reduce the effectiveness of some data analysis techniques and prevent the use of others. This project contains nearest neighbor based tools for the imputation and prediction of these missing values. The code is implemented in Python and uses a nearest neighbor based approach. Two variants are used  a simple weighted nearest neighbors, and a local least squares based regression. Changes:Initial Announcement on mloss.org.

About: OpenGM is a free C++ template library, a command line tool and a set of MATLAB functions for optimization in higher order graphical models. Graphical models of any order and structure can be built either in C++ or in MATLAB, using simple and intuitive commands. These models can be stored in HDF5 files and subjected to stateoftheart optimization algorithms via the OpenGM command line optimizer. All library functions can also be called directly from C++ code. OpenGM realizes the Inference Algorithm Interface (IAI), a concept that makes it easy for programmers to use their own algorithms and factor classes with OpenGM. Changes:Initial Announcement on mloss.org.

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining. Changes:1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "scoreforclass C" causes scores to be computed relative to a given (positive) class. For twoclass problems. Fixed bug in example sampling code (sample n) Fixed bug keeping oldstyle example formats (terminated by dot) from working. More code restructuring.

About: This Java software implements Profile Hidden Markov Models (PHMMs) for protein classification for the WEKA workbench. Standard PHMMs and newly introduced binary PHMMs are used. In addition the software allows propositionalisation of PHMMs. Changes:description changed

About: A Sortware for All Pairs Similarity Search Changes:Initial Announcement on mloss.org.

About: KeplerWeka represents the integration of all the functionality of the WEKA Machine Learning Workbench into the opensource scientific workflow Kepler. Among them are classification, [...] Changes:

About: OpenViBE is an opensource platform that enables to design, test and use BrainComputer Interfaces (BCI). Broadly speaking, OpenViBE can be used in many realtime Neuroscience applications [...] Changes:New release 0.8.0.

About: Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices. Changes:Initial Announcement on mloss.org.

About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the defacto industry standard for matrix computations, and uses stateoftheart implementations like ATLAS for all its computational routines, making jBLAS very fast. Changes:Changes from 1.0:

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.
