31...40 <=30 <=30 >40 <=30 low >40 medium no low yes 31...40 medium medium yes 31...40 high ves medium ves no yes medium no excellent fair fair fair excellent excellent fair excellent yes no yes yes no yes yes ΠΟ Learning Outcome(s): LO2 Instructors: Apply and evaluate data mining algorithms with respect to problems they are specifically designed for Question Three 1.5 Marks Given the testing dataset and the constructed decision tree below. Calculate the accuracy, error rate, sensitivity, specificity, precision, and recall. The model. predicts if a person will buy a computer or not based on his/her information. no no age <=30 <=30 <-30 >40 student? yes income high high 31...40 high yes medium age? 31..40 yes student no ΠΟ no no >40 credit rating? excellent fair no credit rating buys.computer fair excellent fair yes fair no no yes no
31...40 <=30 <=30 >40 <=30 low >40 medium no low yes 31...40 medium medium yes 31...40 high ves medium ves no yes medium no excellent fair fair fair excellent excellent fair excellent yes no yes yes no yes yes ΠΟ Learning Outcome(s): LO2 Instructors: Apply and evaluate data mining algorithms with respect to problems they are specifically designed for Question Three 1.5 Marks Given the testing dataset and the constructed decision tree below. Calculate the accuracy, error rate, sensitivity, specificity, precision, and recall. The model. predicts if a person will buy a computer or not based on his/her information. no no age <=30 <=30 <-30 >40 student? yes income high high 31...40 high yes medium age? 31..40 yes student no ΠΟ no no >40 credit rating? excellent fair no credit rating buys.computer fair excellent fair yes fair no no yes no
Operations Research : Applications and Algorithms
4th Edition
ISBN:9780534380588
Author:Wayne L. Winston
Publisher:Wayne L. Winston
Chapter19: Probabilistic Dynamic Programming
Section19.4: Further Examples Of Probabilistic Dynamic Programming Formulations
Problem 7P
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Given the testing dataset and the constructed decision tree below. Calculate the accuracy, error rate, sensitivity, specificity, precision, and recall. The model predicts if a person will buy a computer or not based on his/her information.
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