Explain the pros & cons of each strategy and provide clear examples when each strategy should...

 

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Explain the pros & cons of each strategy and provide clear examples when each strategy should be chosen and why: (A) Decision/Classification Tree (B) Maximal Margin Classifier (MMC) (C) SVM - linear kernel (or SVC) (D) SVM - polynomial kernel (E) SVM - radial kernel Explain the pros & cons of each strategy and provide clear examples when each strategy should be chosen and why: (A) Decision/Classification Tree (B) Maximal Margin Classifier (MMC) (C) SVM - linear kernel (or SVC) (D) SVM - polynomial kernel (E) SVM - radial kernel

Answer rating: 100% (QA)

The pros cons of decisionclassification tree Pros Cons Easy for interpret and are best suited for visual representation Example white box model Here c... View the full answer