Artifacts using Weka Dev (257)

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An extensible web page segmentation and analysis framework - Classification algorithms.

DKPro Similarity Algorithms ML GPL

Contains meta-filter/-classifier/-cluster to get access to the data that is being used.

LIMES Core Library

A collection of multi-instance learning classifiers. Includes the Citation KNN method, several variants of the diverse density method, support vector machines for multi-instance learning, simple wrappers for applying standard propositional learners to multi-instance data, decision tree and rule learners, and some other methods.

Massive On-line Analysis is an environment for massive data mining. MOA provides a framework for data stream mining and includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, also written in Java, while scaling to more demanding problems. ADAMS fork.

CSV loader/saver that handles common CSV formats.

Common classes for MedGIFT ePad plugins, Web Services, etc.

Simple learning schemes for educational purposes (Prism, Id3, IB1 and NaiveBayesSimple).

Class implementing a HyperPipe classifier. For each category a HyperPipe is constructed that contains all points of that category (essentially records the attribute bounds observed for each category). Test instances are classified according to the category that "most contains the instance". Does not handle numeric class, or missing values in test cases. Extremely simple algorithm, but has the advantage of being extremely fast, and works quite well when you have "smegloads" of attributes.