About: Bayesian Additive Regression Trees

Fetched by r-cran-robot on 2018-09-01 00:00:04.021726

About: Mining Association Rules and Frequent Itemsets

Fetched by r-cran-robot on 2018-09-01 00:00:03.513366

About: Classification, Regression and Feature Evaluation

Fetched by r-cran-robot on 2018-01-01 00:00:07.164852

About: Extending Lasso Model Fitting to Big Data

Fetched by r-cran-robot on 2018-09-01 00:00:04.365069

About: A Content Anomaly Detector based on n-Grams

A teeny tiny fix to correctly handle input strings shorter than a registers width

About: A Tool for Measuring String Similarity

This release fixes the incorrect implementation of the bag distance.

About: Big Random Forests

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

About: peewit provides services for programming, running and result examination of machine learning experiments. It does not include any ML algorithms, has no GUI, and presumes certain uniformity of the experimental layout. But it does not make assumptions on the type of task under study. The current version-number is 0.10.

v-cube with side-cubes

About: Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics:

Diff URL: https://github.com/idiap/bob/compare/v1.1.4...HEAD Commits: 629 Files changed: 954 Contributors: 7

Here is a quick list of things you should pay attention for while integrating your satellite packages against Bob 1.2.x:

• The LBP module had its API changed look at the online docs for more details
• LLRTrainer has been renamed to CGLogRegTrainer
• The order in which you pass data to CGLogRegTrainer has been inverted (negatives now go first)
• For C++ bindings, includes are in bob/python instead of bob/core/python
• All specialized Bob exceptions are gone, if you were catching them, most have been cast into std::runtime_error's

For a detailed list of changes and additions, please look at our Changelog page for this release and minor updates:

https://github.com/idiap/bob/wiki/Changelog-from-1.1.4-to-1.2 https://github.com/idiap/bob/wiki/Changelog-from-1.2.0-to-1.2.1 https://github.com/idiap/bob/wiki/Changelog-from-1.2.1-to-1.2.2

About: a dbms for resonating neural networks. Create and use different types of machine learning algorithms.

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 bug-fixes and speed improvements

About: An open source Java software providing collaborative filtering algorithms.

Initial Announcement on mloss.org.

About: R version of GENetic Optimization Using Derivatives

Fetched by r-cran-robot on 2013-04-01 00:00:08.101900

About: Oblique Trees for Classification Data

Fetched by r-cran-robot on 2013-04-01 00:00:06.648184

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: Rule- and Instance-Based Regression Modeling

Fetched by r-cran-robot on 2011-08-28 08:16:03.375532

About: Tools to convert datasets from various formats to various formats, performance measures and API functions to communicate with mldata.org

• Change task file format, such that data splits can have a variable number items and put into up to 256 categories of training/validation/test/not used/...
• Various bugfixes.

About: KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages. At the moment, KReator supports Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), Relational Bayesian Networks (RBN), and Probabilistic Prolog (ProbLog).

• several bugfixes
• Beta version of ProbLog plugin
• enhanced command completion in console
• enhanced error messages for syntax errors
• refactored logic libraries
• added prettyprint function in console
• added syntax highlighting for RBNs

About: GIDOC (Gimp-based Interactive transcription of old text DOCuments) is a computer-assisted transcription prototype for handwritten text in old documents. It is a first attempt to provide integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. GIDOC is built on top of the well-known GNU Image Manipulation Program (GIMP), and uses standard techniques and tools for handwritten text preprocessing and feature extraction, HMM-based image modelling, and language modelling.

Updated version for mloss 2010