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prediction is made to a new observation X(C, S) having X1=C and X2=S. Obs 1 2- 3 4 5 67= 8- 9 10 11- 12 13 14 15| 16 17 18 19 20 X1e A« A« A- A« A« B« B< B- B« Be Ce C- C- C- C= D« D« D« D« DeE X2- S M« M« S- S< S« M« M L« Le Le M M Le Le S- M« Le Se M- Ye 0< 0- 1 14 0€ 0- 0€ 14 14 1e 1e 1e 1e 1e 0-| 0-1e| 1e 1ª 04 (a) By applying Laplace Smoothing with Laplace-k estimate k=2, calculate the following: P(Y=1) =? P(X1=A|Y=1) = ? P(X1=A|Y=0) = ? P(X2=S[Y=1) = ? P(X2=M[Y=0) = ? P(Y=0) = ?« P(X1=B|Y=1) = ? P(X1=C|Y=1)=? P(X1=B|Y=0) = ? P(X1=C|Y=0) = ? P(X2=M|Y=1) = ? P(X2=L|Y=1) =? P(X2=L[Y=0) = ?< P(X1=D[Y=1) = ?d P(X1=D|Y=0) = ?« P(X2=S|Y=0) = ? (b) Does the new observation X(C, S) belong to class Y=0 or Y=1? You must show your working steps in answering this question.

prediction is made to a new observation X(C, S) having X1=C and X2=S. Obs 1 2- 3 4 5 67= 8- 9 10 11- 12 13 14 15| 16 17 18 19 20 X1e A« A« A- A« A« B« B< B- B« Be Ce C- C- C- C= D« D« D« D« DeE X2- S M« M« S- S< S« M« M L« Le Le M M Le Le S- M« Le Se M- Ye 0< 0- 1 14 0€ 0- 0€ 14 14 1e 1e 1e 1e 1e 0-| 0-1e| 1e 1ª 04 (a) By applying Laplace Smoothing with Laplace-k estimate k=2, calculate the following: P(Y=1) =? P(X1=A|Y=1) = ? P(X1=A|Y=0) = ? P(X2=S[Y=1) = ? P(X2=M[Y=0) = ? P(Y=0) = ?« P(X1=B|Y=1) = ? P(X1=C|Y=1)=? P(X1=B|Y=0) = ? P(X1=C|Y=0) = ? P(X2=M|Y=1) = ? P(X2=L|Y=1) =? P(X2=L[Y=0) = ?< P(X1=D[Y=1) = ?d P(X1=D|Y=0) = ?« P(X2=S|Y=0) = ? (b) Does the new observation X(C, S) belong to class Y=0 or Y=1? You must show your working steps in answering this question.

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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20 observations in the table below are used to train a Naïve Bayes model, and then a prediction is made to a new observation X(C, S) having X1=C and X2=S. Obs 14 2- 3 45 6- 7- 8- 9 10 11 12 13 14 15 16 17 18 19 20 X1e A A A A A B B- B- B Be Ce Ce Ce Ce Ce De DE De DE De X2e se M M S se se M M Le Le Le Me M L- Le se Me Le se Me Ye 04 0- 1e 14 04 04 0 1e 14 1e 1e 1e 1e 1e 0e 0 1e 1e 14 0eE (a) By applying Laplace Smoothing with Laplace-k estimate k=2, calculate the following: - P(Y=1) = ? P(X1=A|Y=1) = ? P(X1=A|Y=0) = ? P(X2=S|Y=1) = ? P(X2=M[Y=0) = ? P(Y=0) = ? P(X1=B|Y=1) = ? P(X1=C|Y=1) =? P(X1=B|Y=0) = ? P(X1=C[Y=0) = ? P(X2=M|Y=1) = ? P(X2=L[Y=1) =? P(X2=L[Y=0) = ?e P(X1=D[Y=1) = ?« P(X1=D|Y=0) = ?« P(X2=S|Y=0) = ?H (b) Does the new observation X(C, S) belong to class Y=0 or Y=1? You must show your working steps in answering this question.
Transcribed Image Text:20 observations in the table below are used to train a Naïve Bayes model, and then a prediction is made to a new observation X(C, S) having X1=C and X2=S. Obs 14 2- 3 45 6- 7- 8- 9 10 11 12 13 14 15 16 17 18 19 20 X1e A A A A A B B- B- B Be Ce Ce Ce Ce Ce De DE De DE De X2e se M M S se se M M Le Le Le Me M L- Le se Me Le se Me Ye 04 0- 1e 14 04 04 0 1e 14 1e 1e 1e 1e 1e 0e 0 1e 1e 14 0eE (a) By applying Laplace Smoothing with Laplace-k estimate k=2, calculate the following: - P(Y=1) = ? P(X1=A|Y=1) = ? P(X1=A|Y=0) = ? P(X2=S|Y=1) = ? P(X2=M[Y=0) = ? P(Y=0) = ? P(X1=B|Y=1) = ? P(X1=C|Y=1) =? P(X1=B|Y=0) = ? P(X1=C[Y=0) = ? P(X2=M|Y=1) = ? P(X2=L[Y=1) =? P(X2=L[Y=0) = ?e P(X1=D[Y=1) = ?« P(X1=D|Y=0) = ?« P(X2=S|Y=0) = ?H (b) Does the new observation X(C, S) belong to class Y=0 or Y=1? You must show your working steps in answering this question.
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