About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:
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About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:
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About: The Advanced Data mining And Machine learning System (ADAMS) is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes. Changes:Some highlights:
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About: Automatically finds the best model with its best parameter settings for a given classification or regression task. Changes:Initial Announcement on mloss.org.
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About: Easily prototype WEKA classifiers and filters using Python scripts. Changes:0.3.0
0.2.1
0.2.0
0.1.1
0.1.0
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About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license. Changes:New version November 2013
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About: Tools to convert datasets from various formats to various formats, performance measures and API functions to communicate with mldata.org Changes:
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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
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