![[10 Points] Assume the Bayesian belief network for the diagnosis of cars electrical system. Battery Radio Lights Ignition Ga](http://img.homeworklib.com/images/3f5db5fe-f14e-47ac-8b75-951862689ac5.png?x-oss-process=image/resize,w_560)
Homework Answers
Answer:
a)
Radio, lights and ignition depends on the functioning of the battery, if battery is working, only then these three will work, but 3 of them are mutually independent.(Conditional independent)
The Gas is marginally independent of all.
b)
We need 7 probabilities to define the full joint distribution.
Number of free parameters =2
c) \
Radio will work if battery is working so P(Radio works/Battery working)
Similarly, P(light works/Battery working)
P(Ignition works/Battery working)
P(Engine starts/(ignition works and Gas)
P(Car moves/engine starts)
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[10 Points] Assume the Bayesian belief network for the diagnosis of car's electrical system. Battery Radio Lights I...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pa30) 0.25 pla-30-50) 0.40 p(s-male)-0.5...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pa30) 0.25 pla-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Age Jewelry Gas plg yeslf yes)-0.2 pg-yesy-no) = 0.01 pi yeslfyes,a s0.05 pi yesf no,a 30,s-male) 0.0001 pi yeslf-no,a 30-50,s-male) 0.0004 PV=yeslf-no,a=>50,s= male) = 0.0002 pi yeslf-no,a 30,s female) 0..0005 py-yeslf-no,a-30-50.5 emale) = 0.002 pi yesf no,a 50,s female) 0.001 Arcs (arrows) are drawn from cause to effect, eg., the stolen card used for either gas or jewelry. It means...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud: pla <30)-0.25 pla-30-50)-0.40 ps-male)-o.s p(-yes)-0.00001 Fraud Age Sex Jewelry pig yeslf-yes)-0.2 pig yeslf...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud: pla <30)-0.25 pla-30-50)-0.40 ps-male)-o.s p(-yes)-0.00001 Fraud Age Sex Jewelry pig yeslf-yes)-0.2 pig yeslf-no)-0.01 pU yeslf-no,a 30,s-male)-0.0001 PV=yesV-no,a-30-50.5-male)-0.0004 PV "yes f-no,a =>50.5-male) = 0.0002 pf yesfeno,a 30,s female)-0.0005 PU =yes ir-no,a-30-50.5-emale) = 0.002 PV=yesy-noa->50.5-female) = 0.001 Arcs (arrows) are drawn from cause to effect, eg., the stolen card used for either gas or jewelry. It means that the current effect is dependent only on its parent node, which represents its...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pla-<30)-0.25 p(a-30-50) 0.40 pf-yes)-0.00001 p(s-male-0.5 Fraud Sex Jewe Gas pi-yesf yes,a 0.0s po yeslf no,a...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pla-<30)-0.25 p(a-30-50) 0.40 pf-yes)-0.00001 p(s-male-0.5 Fraud Sex Jewe Gas pi-yesf yes,a 0.0s po yeslf no,a-30,s-male)-0.0001 pG yeslf-no,a-30-50,s-male) -0.0004 po yeslf no,a->50,s-male)-0.0002 po yesf no,a 30,s Jemale)-0.0005 pi yesf no,a 30-50,s female) 0.002 pi yes no,a >50,s female)-0.00 p(g yesf yes) 0.2 pg-yes|f=no) = 0.01 Arcs (arrows) are drawn from cause to effect, e.g., the stolen card used for either gas or jewelry. It means that the current effect is...
Consider the following Bayesian network for detecting credit-card fraud: pla 30)- 0.25 p(a-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Jewelry Jas PV-veslf-yes, a= *s= *) = 0.05 PV-yesy-no,...
Consider the following Bayesian network for detecting credit-card fraud: pla 30)- 0.25 p(a-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Jewelry Jas PV-veslf-yes, a= *s= *) = 0.05 PV-yesy-no, a=<30,s-male) = 0..000 I pi-yeslf no,a-30-50,s-male)- 0.0004 pj-yeslf no,a-50,s-male) 0.0002 p-yeslf no,a-<30,s-female) -0.0005 p(j=ves-no,a-30-50's-female) = 0.002 p(g yeslf-yes)-0.2 plg yes no 0.01 Arcs (arrows) are drawn from cause to effect, e.g., the stolen card used for either gas or jewelry. It means that the current effect is dependent only on its parent...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pa30) 0.25 pla-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Age Jewelry Gas plg yeslf yes)-0.2 pg-yesy-no)...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pa30) 0.25 pla-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Age Jewelry Gas plg yeslf yes)-0.2 pg-yesy-no) = 0.01 pi yeslfyes,a s0.05 pi yesf no,a 30,s-male) 0.0001 pi yeslf-no,a 30-50,s-male) 0.0004 PV=yeslf-no,a=>50,s= male) = 0.0002 pi yeslf-no,a 30,s female) 0..0005 py-yeslf-no,a-30-50.5 emale) = 0.002 pi yesf no,a 50,s female) 0.001 Arcs (arrows) are drawn from cause to effect, eg., the stolen card used for either gas or jewelry. It means...
Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pa30) 0.25 pla-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Age Jewelry Gas plg yeslf yes)-0.2 pg-yesy-no) = 0.01 pi yeslfyes,a s0.05 pi yesf no,a 30,s-male) 0.0001 pi yeslf-no,a 30-50,s-male) 0.0004 PV=yeslf-no,a=>50,s= male) = 0.0002 pi yeslf-no,a 30,s female) 0..0005 py-yeslf-no,a-30-50.5 emale) = 0.002 pi yesf no,a 50,s female) 0.001 Arcs (arrows) are drawn from cause to effect, eg., the stolen card used for either gas or jewelry. It means...
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Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pla-<30)-0.25 p(a-30-50) 0.40 pf-yes)-0.00001 p(s-male-0.5 Fraud Sex Jewe Gas pi-yesf yes,a 0.0s po yeslf no,a-30,s-male)-0.0001 pG yeslf-no,a-30-50,s-male) -0.0004 po yeslf no,a->50,s-male)-0.0002 po yesf no,a 30,s Jemale)-0.0005 pi yesf no,a 30-50,s female) 0.002 pi yes no,a >50,s female)-0.00 p(g yesf yes) 0.2 pg-yes|f=no) = 0.01 Arcs (arrows) are drawn from cause to effect, e.g., the stolen card used for either gas or jewelry. It means that the current effect is...
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Problem 2 Consider the following Bayesian network for detecting credit-card fraud Pa30) 0.25 pla-30-50) 0.40 p(s-male)-0.5 p(f-yes) 0.00001 Fraud Sex Age Jewelry Gas plg yeslf yes)-0.2 pg-yesy-no) = 0.01 pi yeslfyes,a s0.05 pi yesf no,a 30,s-male) 0.0001 pi yeslf-no,a 30-50,s-male) 0.0004 PV=yeslf-no,a=>50,s= male) = 0.0002 pi yeslf-no,a 30,s female) 0..0005 py-yeslf-no,a-30-50.5 emale) = 0.002 pi yesf no,a 50,s female) 0.001 Arcs (arrows) are drawn from cause to effect, eg., the stolen card used for either gas or jewelry. It means...
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