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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

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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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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31...40 low <=30 <=30 >40 <=30 31...40 medium >40 low yes no yes medium yes medium yes medium medium no 31...40 high yes no excellent fair fair fair excellent excellent fair excellent yes no yes yes no yes ves no Learning Outcome(s): LO2 Instructors: Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. J Question Three 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 31...40 >40 >40 >40 <=30 student? yes income high high high yes medium low low age? 31..40 yes student no no no no yes yes >40 excellent no credit rating? fair excellent fair credit rating buys computer fair fair fair excellent yes no no yes no yes (₁ no 1.5 Marks
Transcribed Image Text:31...40 low <=30 <=30 >40 <=30 31...40 medium >40 low yes no yes medium yes medium yes medium medium no 31...40 high yes no excellent fair fair fair excellent excellent fair excellent yes no yes yes no yes ves no Learning Outcome(s): LO2 Instructors: Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. J Question Three 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 31...40 >40 >40 >40 <=30 student? yes income high high high yes medium low low age? 31..40 yes student no no no no yes yes >40 excellent no credit rating? fair excellent fair credit rating buys computer fair fair fair excellent yes no no yes no yes (₁ no 1.5 Marks
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