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batcat
Posts: 11
Posted 18:56 Aug 25, 2009 |

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p0941
Posts: 95
Posted 12:26 Aug 26, 2009 |

Only one comment.  The naive bayesian classification fails where the training data pool is too small to add one to zero as numerator and to denominator. 

xieguahu
Posts: 50
Posted 15:40 Aug 26, 2009 |

For the test record 2,

The final calculation should be

P(fish | X2) = (a) x (1/12) x ( .5) = .042a

batcat
Posts: 11
Posted 22:32 Aug 26, 2009 |
xieguahu wrote:

For the test record 2,

The final calculation should be

P(fish | X2) = (a) x (1/12) x ( .5) = .042a

I don't think I agree.

The probability of class fish is 2/12 not 1/12

HelloWorld
Posts: 88
Posted 18:17 Aug 29, 2009 |
batcat wrote:

See attachment

Confirming this answer is right..

alomo
Posts: 70
Posted 16:39 Aug 30, 2009 |
batcat wrote:

See attachment

Could you explain why in P(X2|reptile) = ... = 2/3 x 2/3 x 2/3 x 0/3 = 0

I am getting 3/3 x 3/3 x 3/3 x 0/3. It will not change the result, but why 2/3 and not 3/3?

HelloWorld
Posts: 88
Posted 16:51 Aug 30, 2009 |
alomo wrote:
batcat wrote:

See attachment

Could you explain why in P(X2|reptile) = ... = 2/3 x 2/3 x 2/3 x 0/3 = 0

I am getting 3/3 x 3/3 x 3/3 x 0/3. It will not change the result, but why 2/3 and not 3/3?

I got the same with you

P(X2 | Reptile) = P(Body Temperature = cold-blooded | Reptile) x P(Skin Cover = scales | Reptile) x P(Gives Birth = no | Reptile) x P(Aquatic Creature = yes | Reptile) x P(Aerial Creature = no | Reptile) x P(Has Legs = no | Reptile) x P(Hibernates = no | Reptile) = 3/3 x 3/3 x 3/3 x 0/3 = 0

batcat
Posts: 11
Posted 17:20 Aug 30, 2009 |

Yes sorry those were all typos

Should be 3/3's not 2/3's

cysun
Posts: 2935
Posted 16:36 Aug 31, 2009 |
p0941 wrote:

Only one comment.  The naive bayesian classification fails where the training data pool is too small to add one to zero as numerator and to denominator. 

p0941 is correct. We cannot let one zero term to zero out all others. The way to deal with this is to add 1 to all counts - if the sample size is sufficiently large, adding one would not affect the results. Sorry I forgot to mention this in the class.

p0941
Posts: 95
Posted 23:44 Aug 31, 2009 |
cysun wrote:
p0941 wrote:

Only one comment.  The naive bayesian classification fails where the training data pool is too small to add one to zero as numerator and to denominator. 

p0941 is correct. We cannot let one zero term to zero out all others. The way to deal with this is to add 1 to all counts - if the sample size is sufficiently large, adding one would not affect the results. Sorry I forgot to mention this in the class.

As I can remember you did talk about this in the class