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Bayes Optimal Classifier: could guide a robot to move either Forward(F) or Left(L) or Right(R): • Let there be 5 hypotheses hi through hs that P(h,|D) P(F\h,) P(L|h,) | P(R|h,) 0.4 0.2 0. 0.1 0. 0.1 0.2 0. Compute the MAP cstimate and Bayes optimal cstimate using the data provided in the table. Are they the same? Justify your answer.

Bayes Optimal Classifier: could guide a robot to move either Forward(F) or Left(L) or Right(R): • Let there be 5 hypotheses hi through hs that P(h,|D) P(F\h,) P(L|h,) | P(R|h,) 0.4 0.2 0. 0.1 0. 0.1 0.2 0. Compute the MAP cstimate and Bayes optimal cstimate using the data provided in the table. Are they the same? Justify your answer.

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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2. Bayes Optimal Classifier: could guide a robot to move either Forward(F) or Left(L) or Right(R): * Let there be 5 hypotheses hy through hs that P(h, D) P(Fh,) P(Lh) P(Rh.) 0.4 0.2 0.1 0.1 0.2 1 0. 0. 0. Compute the MAP estimate and Bayes optimal estimate using the data provided in the table. Are they the same? Justify your answer.
Transcribed Image Text:2. Bayes Optimal Classifier: could guide a robot to move either Forward(F) or Left(L) or Right(R): * Let there be 5 hypotheses hy through hs that P(h, D) P(Fh,) P(Lh) P(Rh.) 0.4 0.2 0.1 0.1 0.2 1 0. 0. 0. Compute the MAP estimate and Bayes optimal estimate using the data provided in the table. Are they the same? Justify your answer.
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