The bayes-network tag has no wiki summary.
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Bayesian network inference using pymc (Beginner's confusion)
I am currently taking the PGM course by Daphne Koller on Coursera. In that, we generally model a Bayesian Network as a cause and effect directed graph of the variables which are part of the observed ...
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32 views
Bayesian belief network for finding combinatory effects of multiple environmental variables on allele frequency
I'm a beginner to Bayesian belief network (BBN). I read a few articles on introduction to BBN. So I know a general idea of BBN. But I'm struggling to construct a graphical network and conditional ...
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18 views
Step by step example of calculation of posterior probabilities for Bayesian network?
I am learning Bayesian networks. I am getting difficulties in understanding computation part of posterior probabilities. If there is any ready made step by step example then it would be really ...
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53 views
Causal models in pymc3
I'm trying to fit a causal model. Participants in a task are trained on the model then asked for their belief in all the joints over the variables (e.g., what are the chances of observing an item with ...
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20 views
Evidential reasoning in Gaussian Bayesian Networks
I am working on Gaussian Bayesian Networks (GBN) i.e. the Bayesian Networks where all the random variables are continuous in nature. I am seriously trapped in the problem of evidential reasoning in ...
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1answer
25 views
How was this summation performed?
Say I have the following simple Bayesian network involving 3 r.v.s A, B, and C:
$$
A \rightarrow C \rightarrow B
$$
I am trying to prove that A and B are conditionally independent given by ...
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1answer
45 views
Latent variables in Bayes nets with no physical interpretation
In Pattern Recognition and Machine Learning Bishop writes about Bayes networks:
For practical applications of probabilistic models, it will typically
be the highernumbered variables ...
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1answer
63 views
Are probability graphic models useful for predictive modelling?
Are Probability Graphic Models (say specifically Bayesian Networks) useful for predictive modelling in terms of large data (100,000 - 1,000,000 rows) and many variables (hundreds)?
Meaning, is this ...
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48 views
Static Bayesian networks using p-values
In your opinion, what is the best way of handling Bayesian networks using continuous data, in this particular case, p-values?
I have read about several discretization techniques, Gaussian approaches, ...
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1answer
94 views
Moralization and triangulization on belief networks
Assume that I have a belief network with a set of nodes.
In order to create a valid junction tree I have to moralize the graph. Assume now that I have nodes with more than 2 parents (e.g 3 parents) ...
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58 views
Learn a joint distribution from incomplete samples
Suppose I want to learn a joint distribution $p(x_1, \ldots, x_n)$ and have a collection of samples $x^k_1, \ldots, x^k_n$ for each $k$. Assume some values $x^k_i$ are unknown, so the samples are ...
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75 views
Bayesian Network parameter Estimation
I am doing a project in which I need to estimate the parameters(Conditional Probabilities) for a bayesian network. I am estimating the parameters from the given sample and using the dirichlet prior. ...
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55 views
Latent groups in Bayes net with BUGS
I'm modeling a Bayes net with OpenBUGS, and I find problems to specify some of the parameters and their priors.
The aim of the model is to identify latent groups in the data from a sample of human ...
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40 views
Using Bayesian Networks to Understand Expected Revenue
I'm trying to understand Bayesian Networks and am attempting to apply it to solve some problems in the world of marketing, most notably search engine marketing. I have a data on EACH in click to a ...
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32 views
Normalization for dynamic Bayesian network inference?
I would like to know whether preprocessing of the dataset is required for dynamic Bayesian network inference or not?
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76 views
Odd results from Bayesian network in R
Related to question here.
I've been trying to teach myself about Network Analysis, and developing DAG charts in R. Let's say that I have the following data.
...
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1answer
562 views
Prediction with Bayesian networks in R
I've been trying to teach myself about Network Analysis, and I've been able to develop DAG charts in R. However, I've looked through three or four R packages and have seen little in the way to a ...
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1answer
589 views
How to write a poker player using Bayes networks
This is my first question on stackexchange and also my first time implementing a Bayesian network so I will apologize ahead of time for any novice mistakes I make.
The goal of my project is to ...
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98 views
Observation (evidence) in dynamic Bayesian networks
I am wondering how the probabilities of the observation nodes in dynamic Bayesian networks are set.
I want to know whether the probabilities are monitored or are given by sensors?
So, what does the ...
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35 views
Empirical change of DAG for Bayesian Network
While working on some problem in bioinformatics I applied bayesian network algorithm for classification purposes. As predictors I took a window of sequence of aminoacids and for dependent variable I ...
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2answers
285 views
Bayes Network/Conditional Probability Visualization Tools
I'm hoping that someone could suggest a tool for viewing conditional probabilities withi. I am currently using Weka, but the ability to view the conditional probability tables of nodes within the ...
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44 views
Updating beliefs networks when new event occur in the future
I'm beginner with the Bayesian networks and I want to know how the beliefs networks update the posterior probabilities when new event occurs in the future.
I want to test an example, I am starting ...
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2answers
97 views
Updating the probability distribution when removing links from a Bayesian network
I have spent a fair amount of time trying to solve this problem but I can't find the solution. More specifically, I have the following matrix:
...
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1answer
437 views
How to calculate joint probabilities from conditional probabilities in a Bayesian Network?
This question is about Bayesian Networks. I want to calculate the probability for certain events to be in a certain state knowing all conditional probabilities.
Consider that I am totally new to ...
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1answer
212 views
Summation of conditional probability in Bayesian network
I have the joint distribution of the bayesian network defined as
$P(CERFD)=P(C)\times P(R)\times P(E|CR) \times P(F|E) \times P(D|F)$
and I am trying to calculate $P(D=d|C=c)$, below are my ...
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1answer
145 views
Is a Bayesian network doing feature selection?
I have just started playing around and reading about Bayes Nets. Here is a snippet of code using the bnlearn package in R, which seems to be a fantastic tool.
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61 views
What value a Bayesian Net?
For those of us that work in data mining building predictive models what is the benefit of a Bayesian belief net? I am sure I am just naive as I have not studied them in depth, but what are the ...
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1answer
529 views
Markov blanket vs normal dependency in a Bayesian network
While I was reading about Bayesian networks, I run into "Markov blanket" term and got severely confused with its independency in a Bayesian network graph.
Markov blanket briefly says that every ...
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3answers
394 views
Probabilistic graphical models textbook
Is Koller's "Probabilistic Graphical Models" suitable as a textbook? Or is there another book which is more recommendable as textbook for a master-course?
Disclaimer: cross-posted from quora.com, ...
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1answer
395 views
Number of parameters for discrete Bayes network?
Suppose $X_1, ..., X_n$ are $d$-ary discrete random variables which are part of a Bayes network, in which $X_i$ has $n_i$ parents. What is the number of parameters for the Bayes network?
