The Apache MADlib team is pleased to announce the immediate availability of the 1.12 release.
This is the project's initial release as an Apache Top Level Project. The main goals of this release are: * New modules (All Pairs Shortest Path, Weakly Connected Components, Breadth First Search, Mulitple Graph Measures, Stratified Sampling, Train-test split, Multilayer Perceptron) * Decision tree and random forest improvements (Allow expressions in feature list, Allow array input for features, Filter NULL dependent values in OOB, Add option to treat NULL as category) * Summary improvements (Allow user to determine the number of columns per run, Improve efficiency of computation time by ~35%) * Sketch improvements (Promote cardinality estimators to top level module from early stage) * Add basic code coverage support * Updates for Apache Top Level Project * Multiple bug fixes All release changes can be found here: https://cwiki.apache.org/confluence/display/MADLIB/MADlib+1.12 You can download the source release and convenience binary packages from Apache MADlib's download page here: http://madlib.apache.org/download.html Alternatively, you can download through an ASF mirror near you: https://www.apache.org/dyn/closer.lua/madlib/1.12 ---- Apache MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data. The MADlib mission: to foster widespread development of scalable analytic skills, by harnessing efforts from commercial practice, academic research, and open-source development. We welcome your help and feedback. For more information on how to report problems, and to get involved, visit the project website at https://madlib.apache.org ---- Thank you, everyone who contributed to the 1.12 release. We look forward to continued community participation for the next release, Apache MADlib v2.0! Regards, Ed Espino
