NeC4.5 —— Neural Ensemble Based C4.5

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Presentation transcript:

NeC4.5 —— Neural Ensemble Based C4.5 Author Yuan Jiang ，Zhi-hua Zhou Reporter Zhen-xing Ge

Why NeC4.5 Comprehensibility Generalization

Some about C4.5 What is C4.5? Pseudocode

Gain-ratio Info_gain Disadvantage： gain-ratio Attribute that has most types. gain-ratio Attribute that has fewer types.

Why C4.5? Handling both continuous and discrete attributes Handling training data with missing attribute values Handling attributes with differing costs. Pruning trees after creation

NeC4.5 Introduction: Train a neural network ensemble. Enlarge the training set. Get the decision tree. Pseudocode:

Pseudocode:

Why NeC4.5?

Thanks for listening！