Showing Items 341350 of 519 on page 35 of 52: First Previous 30 31 32 33 34 35 36 37 38 39 40 Next Last
About: Given many points in ROC (Receiver Operator Characteristics) space, computes the convex hull. Changes:Initial Announcement on mloss.org.

About: Generalised Stirling Numbers for PitmanYor Processes: this library provides ways of computing generalised 2ndorder Stirling numbers for PitmanYor and Dirichlet processes. Included is a tester and parameter optimiser. This accompanies Buntine and Hutter's article: http://arxiv.org/abs/1007.0296, and a series of papers by Buntine and students at NICTA and ANU. Changes:Moved repository to GitHub, and added thread support to use the main table lookups in multithreaded code.

About: Multiclass vector classification based on cost functiondriven learning vector quantization , minimizing misclassification. Changes:Initial Announcement on mloss.org.

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. Changes:o citation update o plot function improved

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications. Changes:

About: a dbms for resonating neural networks. Create and use different types of machine learning algorithms. Changes:AIML compatible (AIML files can be imported); new 'Grid channel' for developing board games; improved topics editor; new demo project: ALice (from AIML); lots of bugfixes and speed improvements

About: The software provides an implementation of a filter/smoother based on Gibbs sampling, which can be used for inference in dynamical systems. Changes:Initial Announcement on mloss.org.

About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "LpLq Sparse Linear and Sparse Multiple Kernel MultiTask Learning". Changes:Initial Announcement on mloss.org.

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: MLwizard recommends and optimizes classification algorithms based on metalearning and is a software wizard fully integrated into RapidMiner but can be used as library as well. Changes:Faster parameter optimization using genetic algorithm with predefined start population.
