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Berikut adalah contoh soal dan pembahasan untuk materi naive bayes dalam decision making
Typology: Exercises
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Nama : Ira Rahmawati (0181031144) 31A P(YES) 9 P(NO) 5 Tugas 3 TPK 14 14
Scenario Outlook Temperature Humidity Wind PlayTenis P(Outlook=Rainy, Play "Yes") P(Outlook=Rainy, Play "No") DAY 1 Sunny Hot High Weak No 3 14 42 3 2 14 28 2 DAY 2 Sunny Hot High Strong No 14 9 126 9 14 5 70 5 DAY 3 Overcast Hot High Weak Yes DAY 4 Rain Mild High Weak Yes P(Temperature=Cool, Play "Yes") P(Temperature=Cool, Play "No") DAY 5 Rain Cool Normal Weak Yes 3 14 42 3 1 14 14 1 DAY 6 Rain Cool Normal Strong No 14 9 126 9 14 5 70 5 DAY 7 Overcast Cool Normal Strong Yes DAY 8 Sunny Mild High Weak No P(Wind=Weak, Play "Yes") P(Wind=Weak, Play "No") DAY 9 Sunny Cool Normal Weak Yes (^6 14 84 6 2 14 28 ) DAY 10 Rain Mild Normal Weak Yes 14 9 126 9 14 5 70 5 DAY 11 Sunny Mild Normal Strong Yes DAY 12 Overcast Mild High Strong Yes P(Humadity=High, Play "Yes") P(Humadity=High, Play "No") DAY 13 Overcast Hot Normal Weak Yes 3 14 42 3 4 14 56 4 DAY 14 Rain Mild High Strong No 14 9 126 9 14 5 70 5
A YES B NO P(C) = P(Class) P(Yes) = 9/14 Yes No P(Yes) P(No) P(No) = 5/14 Sunny 2 3 0,2 0, Overcast 4 0 0,4 0 Rainy 3 2 0,3 0, Total 9 5 100% 100%
Yes No P(Yes) P(No) Cara manual : Hot 2 2 0,2 0,4 Pilihan YES Mild 4 2 0,4 0,4 3/9 X 3/9 X 3/9 X 6/9 X 9/14 = 0. Cool 3 1 0,3 0,2 -> CONVERT KE PERSENTASI Total 9 5 100% 100%
Pilihan NO Yes No P(Yes) P(No) 2/5 X 1/5 X 4/5 X 2/5 X 5/14 = 0. Normal 6 1 0,7 0,2 -> CONVERT KE PERSENTASI High 3 4 0,3 0, Total 9 5 100% 100%
Yes No P(Yes) P(No) Weak 6 2 0,7 0, Strong 3 3 0,3 0, Total 9 5 100% 100%
P(Yes)/P(No) Yes 9 0, No 5 0, Total 14 100%
Wind
Play
X=(Outlook<=Rain, Temperature=Cool, Humidity=High, Wind=Weak)
YES 1,587%
Outlook
Temperature
Humidity
x = ->
x = ->
x = ->
x = ->
x
x
x = -> = 0,
x = ->