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Enhancements to Basic Decision Tree Induction

  • Allow for continuous-valued attributes
    • Dynamically define new discrete-valued attributes that partition the continuous attribute value into a discrete set of intervals
  • Handle missing attribute values
    • Assign the most common value of the attribute
    • Assign probability to each of the possible values
  • Attribute construction
    • Create new attributes based on existing ones that are sparsely represented
    • This reduces fragmentation, repetition, and replication

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