data mining - WEKA

profilerishwanth

 

  1. Clean and prepare the attached data file for use in Weka as an .arff file. Show your steps. (Make sure that the label is in the last column.)
  2. Compare class determination using Random Forest and Random Tree. 
  3. Compare the value of a hold out set to k-fold cross validation for validating the model. Suggest a filter to be used to improve validation results. Explain your answer.. 
  4. For one model, find the weakest attribute. Explain how you found it.
  5. Submit all answers and screen shots in one Word Document named DMFinal1_yourname.
  • 2 years ago
  • 10
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