• Created by: smrc
  • Created on: 21-08-19 18:04

To find a clasifier that can map individual data items into one of several pre-defined and non over-lapping classes.

  • SUPERVISED learning method: Labelled records, training data used to define classes.

Classification Tasks:

  • Mortgage
  • Credit Risk
  • Heart Disease

Historical data = training data.

ID3 + data = Decision Tree + Defined Classes

Values of attributes of unseen data compared to values in decision tree, path created to class.

Classification is non-overlapping (usually binary)

DECISION TREE: A classification method used either to calculate probability that a given


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