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Question: Using Naive Bayes classification method (m-estimate of probability), classify the testing data and calculate Accuracy, Precision, and Recall from confusion matrix. Training Dataset Target Attribute Income Student Credit Buys computer high high Age P1 <- 30 fair no no P2 <-30 excellent no no P3 31...40 high fair no yes P4 >40 medium fair no yes P5 >40 low yes fair yes P6 >40 low yes excellent no P7 31...40 low yes excellent yes P8 <-30 medium no fair no P9 <-30 low fair Yes ves

Question: Using Naive Bayes classification method (m-estimate of probability), classify the testing data and calculate Accuracy, Precision, and Recall from confusion matrix. Training Dataset Target Attribute Income Student Credit Buys computer high high Age P1 <- 30 fair no no P2 <-30 excellent no no P3 31...40 high fair no yes P4 >40 medium fair no yes P5 >40 low yes fair yes P6 >40 low yes excellent no P7 31...40 low yes excellent yes P8 <-30 medium no fair no P9 <-30 low fair Yes ves

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Question: Using Naive Bayes classification method (m-estimate of probability), classify the testing data and calculate Accuracy, Precision, and Recall from confusion matrix. Training Dataset Target Attribute Age Income Student Credit Buys computer high high high P1 <=30 no fair no P2 <= 30 excellent no no P3 31...40 fair yes no P4 >40 medium fair yes no P5 fair >40 low yes yes P6 >40 low yes excellent no P7 31..40 low yes excellent yes P8 <- 30 medium fair no no P9 <= 30 low yes fair yes P10 >40 medium yes fair yes <= 30 medium 31...40 medium P11 yes excellent yes P12 excellent yes no P13 31...40 high yes fair yes P14 >40 medium excellent no no Testing Data: Age <=30 Buys computer Income Student Credit R1 High yes fair yes R2 <=30 Low no excellent no R3 31.40 medium no fair no R4 31..40 low yes excellent yes R5 >40 low no fair no R6 >40 high yes excellent yes Subject: Machine Learning 2 2 2 重
Transcribed Image Text:Question: Using Naive Bayes classification method (m-estimate of probability), classify the testing data and calculate Accuracy, Precision, and Recall from confusion matrix. Training Dataset Target Attribute Age Income Student Credit Buys computer high high high P1 <=30 no fair no P2 <= 30 excellent no no P3 31...40 fair yes no P4 >40 medium fair yes no P5 fair >40 low yes yes P6 >40 low yes excellent no P7 31..40 low yes excellent yes P8 <- 30 medium fair no no P9 <= 30 low yes fair yes P10 >40 medium yes fair yes <= 30 medium 31...40 medium P11 yes excellent yes P12 excellent yes no P13 31...40 high yes fair yes P14 >40 medium excellent no no Testing Data: Age <=30 Buys computer Income Student Credit R1 High yes fair yes R2 <=30 Low no excellent no R3 31.40 medium no fair no R4 31..40 low yes excellent yes R5 >40 low no fair no R6 >40 high yes excellent yes Subject: Machine Learning 2 2 2 重
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