Preview | 2009.06.09
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![]() Chris |
For extra credit, find out the P(W|C), since he did not supply us with the probability. You'll also need to know that P(C) = 0.5 and P(W) = 0.3. | |||
P(W|C) = 0.3 |
![]() KO |
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What did CS come up with? Since she is EE, she may have applied Maxwell's equations to solve this dinner conundrum. This is some ill J-Pod humor. | ||||
I got 0.42, P(C|W) * P(W) / P(C) = 0.7 * 0.3 / 0.5 = 0.42 | ||||
Yeah CS, let's see the Bode plot of the W/Chris transfer function. |
![]() Connie |
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My attempt at pseudo-fuzzy interfacing... | ||||
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a=newfis('w_chris_cacluator'); a.input(1).name='w'; a.input(1).range=[0 10]; a.input(1).mf(1).name='no_show'; a.input(1).mf(1).type='gaussmf'; a.input(1).mf(1).params=[1.5 0]; a.input(1).mf(2).name='maybe'; a.input(1).mf(2).type='gaussmf'; a.input(1).mf(2).params=[1.5 5]; a.input(1).mf(3).name='yes'; a.input(1).mf(3).type='gaussmf'; a.input(1).mf(3).params=[1.5 10]; a.input(2).name='chris'; a.input(2).range=[0 10]; a.input(2).mf(1).name='no_show'; a.input(2).mf(1).type='trapmf'; a.input(2).mf(1).params=[-2 0 1 3]; a.input(2).mf(2).name='maybe'; a.input(2).mf(2).type='trapmf'; a.input(2).mf(2).params=[7 9 10 12]; a.output(1).name='dinner'; a.output(1).range=[0 30]; a.output(1).mf(1).name='okay' a.output(1).mf(1).type='trimf'; a.output(1).mf(1).params=[0 5 10]; a.output(1).mf(2).name='average'; a.output(1).mf(2).type='trimf'; a.output(1).mf(2).params=[10 15 20]; a.output(1).mf(3).name='fabulous'; a.output(1).mf(3).type='trimf'; a.output(1).mf(3).params=[20 25 30]; a.rule(1).antecedent=[1 1]; a.rule(1).consequent=[1]; a.rule(1).weight=1; a.rule(1).connection=2; a.rule(2).antecedent=[2 0]; a.rule(2).consequent=[2]; a.rule(2).weight=1; a.rule(2).connection=1; a.rule(3).antecedent=[3 2]; a.rule(3).consequent=[3]; a.rule(3).weight=1; a.rule(3).connection=2
◄ |
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