1. KNIME extension plug-in
    (place it to dropins directory of your knime 2.7 installation)

    • VFDT in KNIME 
      Very Fast Decision Tree for continuous attributes. The VFDT can incorporate and classify new information online, with a single scan of the data, in time constant per example. The most relevant property of our system is the ability to obtain a performance similar to a standard decision tree algorithm even for medium size datasets. This is relevant due to the any-time property. Continuous attributes are handled by binary tree structure.

    • Decision Rules for Streams in KNIME 
      Decision Rules for Streams are designed for high-speed data streams. It is a single pass algorithm, that learns ordered and/or unordered rules. VFDR incrementally processes training examples and induces new rules and specializes existing rules.
  2. MEC for R: 
    This package implements the transition detection algorithm, proposed by Oliveira and Gama (2010), within the MEC framework. This algorithm detects clusters transitions between two snapshots of data. It comprises two different methods, each one devised to monitor changes for distinct types of cluster representation schemes, which can be represented by enumeration or by comprehension.

  3. Classification Rules for Streams in MOA

  4. Regression Rules for Streams in MOA