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Questions tagged [bayes]

For questions related to Thomas Bayes, his work and extension of his work, theory and applications.

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What are the main benefits of using Bayesian networks?

I have some trouble understanding the benefits of Bayesian networks. Am I correct that the key benefit of the network is that one does not need to use chain rule of probability in order to calculate ...
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1answer
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Can we derive the distribution of a random variable based on a dependent random variable's distribution?

In the diagram below, there are three variables: X3 is a function of (depends on) X1 and X2, ...
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How to perform structure learning for Bayes Net given already partially constructed net?

Let assume that we have dataset of variables (random events), I apriori would like to set dependency conditions between some of them and perform structure learning to figure out the rest of the net. ...
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My naive (ha!) Gaussian Naive Bayes classifier is too slow

I am trying to build a film review classifier where I determine if a given review is positive or negative (w/ Python). I'm trying to avoid any other ML libraries so that I can better understand the ...
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2answers
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Heuristic funtion for BayesChess

I am reading BayesChess: A computer chess program based on Bayesian networks (Fernandez, Salmeron; 2008) It is a chess playing engine using Bayesian networks. The following is mentioned about ...
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How to use SLAM on other sensor other than camera?

I have a sensor that reads electromagnetic field strength from each position. And the field is stable and unique for each position. So the reading is simply a function of the position like this: <...
2
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2answers
48 views

How do I combine two electromagnetic readings to predict the position of a sensor?

I have an electromagnetic sensor and electromagnetic field emitter. The sensor will read power from the emitter. I want to predict the position of the sensor using the reading. Let me simplify the ...
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0answers
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Why is Information Filter called Information Filter?

We all know Information Filter is a dual representation of Kalman Filter. The main difference between Information Filter and Kalman Filter is the way the Gaussian belief is represented. In Kalman ...
4
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1answer
189 views

How does the Dempster-Shafer theory of evidence differ from the Bayesian reasoning under uncertainty?

Dempster–Shafer theory (wiki) Bayesian probability (wiki) How do these two methods handle uncertainty in regard to information fusion?
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1answer
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Naive Bayes Algorithm error

In the attached image is the probability with the Naives Bayes algorithm of: Fem:dv/m/s Young own Ex-credpaid Good ->62% I calculated the Probability so: P(Fem:dv/m/s | Good)*P(Young | Good)...
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1answer
107 views

Why is exact inference in bayesian network both NP-hard and P-hard?

I should show that exact inference in bayesian network (BN) is NP-hard and P-hard by using a 3SAT Problem. So I did formulate a 3SAT Problem by defining 3CNF: ...
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2answers
280 views

Are bayesian networks important to learn in 2018?

Hi I study AI by myself with "AI a modern approach" I've just finished the chapters about bayesian network and probabilities, and I found them very interesting. Now I want to implement the differents ...
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Bayes' theorem and implementation in line expression

What is Bayes' theorem and Bayes' error? How is it implemented through line expression in Machine Learning?
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101 views

Naive Bayes explanation of the rule

On books and documents explaining the Naive Bayes generative algorithm I always find the following equation: argmaxy p(y|x) = argmaxy (p(x|y)*p(y)/p(x)) ≈ argmaxy (p(x|y)*p(y)) What I don't ...