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ADTree (3.6)

Analytics Integrations Weka Weka (3.6) Classification Algorithms
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Class for generating an alternating decision tree. The basic algorithm is based on: Freund, Y., Mason, L.: The alternating decision tree learning algorithm. In: Proceeding of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, 124-133, 1999. This version currently only supports two-class problems. The number of boosting iterations needs to be manually tuned to suit the dataset and the desired complexity/accuracy tradeoff. Induction of the trees has been optimized, and heuristic search methods have been introduced to speed learning.

(based on WEKA 3.6)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Node details

Input ports
  1. Type: Table
    Training data
    Training data
Output ports
  1. Type: Weka 3.6 Classifier
    Trained classifier
    Trained classifier

Extension

The ADTree (3.6) node is part of this extension:

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