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

• Move "flow"-related classes into package "de.claas.mosis.flow" (e.g. Node and Link).
• Refined and improved "flow"-related tests (e.g. Iterator and Node tests).
• Refactored tests for data formats (e.g. PlainText and JSON tests).
• Added visitor design pattern for graph-based functions (e.g. initialization and processing).
• Documented parameters of Processor implementations.

About: Bayesian Additive Regression Trees

Fetched by r-cran-robot on 2018-09-01 00:00:03.597464

About: A Matlab benchmarking toolbox for online and adaptive regression with kernels.

• Changes in algorithms' Matlab class format
• New algorithms
• Minor improvements and bug fixes

About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Initial Announcement on mloss.org.

About: Big Random Forests

Fetched by r-cran-robot on 2015-11-01 00:00:04.072762

About: HSSVM is a software for solving multi-class problem using Hyper-sphere Support Vector Machines model, implemented by Java.

1. From this version, the version number is normalized to hssvm1.0.1;
2. In this version, we delete the features about running parameter searching and run-all from Ant script, that is, commands "ant search-param" and "ant run-all" which exist in previous version are no longer available, and they are replaced with commands "svm search conf" and "svm runall conf", both of them are used on Linux(or all other POSIX systems).If you want to use this program on Windows, the cygwin is required to be installed.

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

• minor bugfix

About: Multivariate partitioning

Fetched by r-cran-robot on 2013-04-01 00:00:06.387032

About: A Java Toolbox for Scalable Probabilistic Machine Learning.

• Added sparklink module implementing the integration with Apache Spark. More information here.
• Fluent pattern in latent-variable-models
• Predefined model implementing the concept drift detection

Detailed information can be found in the toolbox's web page

About: ALGLIB is an open source numerical analysis library distributed under GPL 2+. It implements both general numerical algorithms and machine learning algorithms. ALGLIB can be used from C#, C++, FreePascal, VBA and other languages. It is the only numerical analysis library which uses automatic translation to generate source code written in different programming languages with 100% identical functionality.

1. New algorithms implemented: exact and approximate nearest neighbor search using kd-trees, new multidimensional scattered data interpolation/fitting algorithm with O(N·logN) complexity (modified Shepard's method with fast k-NN queries), linear algebra algorithms

2. faster QR/LQ, matrix inversion, condition number estimation.

3. Minor fixes

About: This is the source code of the mloss.org website.

Now works with newer django versions and fixes several warnings and minor bugs underneath. The only user visible change is probably that the subscription and bookmark buttons work again.

About: A header-only C++ library for solving large scale eigenvalue problems

• Fixed regressions in v0.6.1 on some edge cases
• Improved the accuracy of restarting processes in SymEigsSolver and GenEigsSolver
• Code and documentation cleanup

About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more

This version comes with Distributed and Mobile Examples

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Updated to version 0.3.0

About: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS)

Fetched by r-cran-robot on 2012-02-01 00:00:11.194183

About: RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...]

Initial Announcement on mloss.org.

About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; One-shot training for an entire regularization path; Continuous checkpointing; much more

• added ElasticNets as a regularization option
• fixed some segfaults, memory leaks, and out-of-range errors, which were creeping in in some corner cases
• added a couple of I/O optimizations