P(PlayTennis=yes, Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = P(PlayTennis=no, Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = P(PlayTennis=yes|Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = P(PlayTennis-no|Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = { Will the player play tennis on the given day? ✓ [Choose ] 4/9 = 0.444 0.010 3/5 = 0.60 4/5 = 0.80 0.027 0.73 3/9 = 0.33 NO, will most likely not play 2/5 = 0.4 5/14 = 0.36 0.27 YES, will most likely play today

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
Problem 1PE
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Using the naive Bayes classifier approach, decide if a person will/will not play tennis on a day that is:

  • Outlook=rain
  • Temperature=mild
  • Humidity=high
  • Wind=strong

 

Use the "PlayTennis" dataset that was used in class (probabilities.pptx).

 

Calculate the prior probabilities
P(PlayTennis=yes) = 9/14 = 0.64

P(PlayTennis=no) =

Calculate the conditional probabilities
P(Outlook=rain|PlayTennis=yes) =
P(Outlook=rain|PlayTennis=no) =
P(Temperature=mild|PlayTennis=yes) =
P(Temperature=mild|PlayTennis=no) =
P(Humidity=high|PlayTennis=yes) =
P(Humidity=high|PlayTennis=no) =
P(Wind=strong|PlayTennis=yes) =

P(Wind=strong|PlayTennis=no) =

Calculate the joint probabilities (before normalization)
P(PlayTennis=yes, Outlook=rain, Temperature=mild, Humidity=high, Wind=strong) =
P(PlayTennis=no, Outlook=rain, Temperature=mild, Humidity=high, Wind=strong) =

Calculate the conditional probabilities (after normalization)
P(PlayTennis=yes|Outlook=rain, Temperature=mild, Humidity=high, Wind=strong) =
P(PlayTennis=no|Outlook=rain, Temperature=mild, Humidity=high, Wind=strong) =

Based on the above joint probabilities, is the player likely to play tennis on the given day?

Group of answer choices
 
P(PlayTennis=yes, Outlook=rain, Temperature=mild, Humidity=high,
Wind-strong) =
P(PlayTennis=no, Outlook=rain, Temperature=mild, Humidity=high,
Wind-strong) =
P(PlayTennis=yes|Outlook=rain, Temperature=mild, Humidity=high,
Wind-strong) =
P(PlayTennis-no|Outlook=rain, Temperature=mild, Humidity=high,
Wind-strong) = {
Will the player play tennis on the given day?
✓ [Choose ]
4/9 = 0.444
0.010
3/5 = 0.60
4/5 = 0.80
0.027
0.73
3/9 = 0.33
NO, will most likely not play
2/5 = 0.4
5/14 = 0.36
0.27
YES, will most likely play today
Transcribed Image Text:P(PlayTennis=yes, Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = P(PlayTennis=no, Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = P(PlayTennis=yes|Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = P(PlayTennis-no|Outlook=rain, Temperature=mild, Humidity=high, Wind-strong) = { Will the player play tennis on the given day? ✓ [Choose ] 4/9 = 0.444 0.010 3/5 = 0.60 4/5 = 0.80 0.027 0.73 3/9 = 0.33 NO, will most likely not play 2/5 = 0.4 5/14 = 0.36 0.27 YES, will most likely play today
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