Questions tagged [bayesian-networks]

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How can we estimate from data the probabilities for naive Bayesian classifier? [closed]

How can we estimate from data the probabilities for naive Bayesian classifier? I don't really understand this question, does it mean, how probable it is that the features are independent?
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Bayesian network in Python: both construction and sampling

For a project, I need to create synthetic categorical data containing specific dependencies between the attributes. This can be done by sampling from a pre-defined Bayesian Network. After some ...
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13 views

How does Markov Chain Monte Carlo work in a neural network from beginning to end?

I am trying to reason through how this works from the beginning of the neural network model to the end from a high level and I want to make sure my understanding is correct, I have probably ...
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1answer
18 views

How do we define the noisy-MAX canonical aggregator for Bayesian networks?

In the book Probabilistic graphical models - principles and techniques, Daphne Koller and Nir Friedman introduce the noisy-OR canonical model for CPDs (in the independence of causal inference family ...
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1answer
77 views

Make the CNN to say “I don't know”

I am currently working on an image classification problem. To ease the implementation I used transfer learning in Keras with ...
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1answer
28 views

Reversing Naive Bayes to find extreme points of data sets

I'd like to know if this is a sensible idea and if there exist any already formed methods to do this (I'm new to the data science area). Essentially, I have used Naive Bayes to accurately classify ...
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1answer
87 views

*Challenge* Making an algo that learns from a book, and can answer anything about it

I recently took this challenge where I am trying to make a set of algorithms to read any particular book, understand and store the context and subsequently answer any question asked about it. In ways ...
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1answer
34 views

Marginalization of joint distribution

I am trying to understand how you marginalise a joint distribution. In my case I have a fair coin, $P(C) = \frac12$ and a fair dice $P(D) = \frac16$. I am told I win a prize if I flip the coin and ...
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399 views

Bayes net inference in Pyro

I am familiar with Bayes nets (discrete/continuous/hybrid). I recently started to learn basics of Pyro and tried to model simple Bayes nets as Pyro programs. I also noticed the simple example answered ...
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13 views

How to elegantly caclulate probability distribution parameters for a particular random variable given some observed data?

I am using bnlearn package and R to learn Bayesian Network structure and also fit it using Maximum Likelihood estimation(MLE). bn.fit uses MLE to learn[as i understand] a generalized probability ...
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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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34 views

Bayesian Neural net with non probibalistic Data?

Is it possible to construct a Bayesian Neural Network without Probability Distributions as dependent Variable for purpose of predictive modeling? I mean, if id like to Infer on a Specific Value, like ...
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1answer
269 views

What's the difference between probabilistic programming such as pyro and belief networks?

I heard about ubers pyro and stumbled upon this Wikipedia article. As I understand, a bayesian network is the same as a belief network according to this post. Does someone know how these are related?...
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1answer
581 views

Undestanding Bayesian network with OpenMarkov

I downloaded OpenMarkov software for probabilistic graphical models and tried it on mtcars dataset. The ...
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1answer
281 views

How to do hidden variable learning in Bayesian Network with Python?

I learned how to use libpgm in general for Bayesian inference and learning, but I do not understand if I can use it for learning with hidden variable. More precisely, I am trying to implement approach ...
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1answer
5k views

Bayesian networks in scikit-learn?

I am trying to understand and use Bayesian Networks. I see that there are many references to Bayes in scikit-learn API, such as Naive Bayes, Bayesian regression, BayesianGaussianMixture etc. On ...
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1answer
41 views

Probability of event given two depandant events

Is there anyway, to compute the probability of the event given two dependent events? I know that Bayes can help if those events are independent, but what if condition events are dependent?
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2answers
105 views

Which learning algorithms to use in what order - dimensionality reduction, bayesian network structure, regression?

The data is a huge set of observations of dozens of variables, all (potentially, somehow) related to a dichotomous outcome variable, and all (potentially) correlated to each other, or to unknown / ...
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1answer
80 views

How to calculate the Probability for the Unconditional Node in the Bayesian Belief Network?

In the popular example for Bayesian Belief network Burglary Alarm how is the probability for burglary P(B) and earthquake P(E) calculated as 0.001 and 0.002 respectively? Is it an assumption made or ...
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Training with feature metadata - bayesian network (naive bayes) [closed]

I am building a project for fun - reverse astrology! I am making a dataset like: ...
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1answer
32 views

Is the maximum BDeu Bayesian Network always the empty network?

I'm recently reading a paper about Scoring Mechanisms for Bayesian Networks. For the BDeu score, it appears that the maximum possible score of BDeu for Bayesian Network structure learning is zero. ...
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15 views

Create a graphical viz of list of elements residing in a column in desired order [closed]

I have a list of elements in a column. Example: UID.................Flow 1............................qwerty, asdfgh, zxcvbn, poiuyt, lkjhgf, mnbvcx 2............................qpwoei, alskdj, ...
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2answers
1k views

Small amount of training data set for naive Bayes classifier for binary classification

I'm implementing prediction system for young cricketers in ODI format using Naive Bayes classifier. The output of the system is to predict whether the young player is rising star or not. I have ...
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1answer
66 views

Reversed Naive Bayes - likelihood and parameter estimation

What happens if we flip the arrows in a Naive Bayes classifier? To clarify - from what I have found naive Bayes is defined for the following network structure: I'm interested to understand what ...
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2answers
2k views

Applying bayesian methods to a simple neural network

This is a really simple neural network with backprop. If one had to apply bayesian "inferences" to update the weights and biases, what would change in the code. ...
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2answers
130 views

Proceeding with various methods for news recommendation

I am beginner in ML (i have done only Andrew Ng's ML course) and i have to work on news recommendation. I went through this paper which mentions different methods used for news recommendation (at 7th ...
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3answers
1k views

Libraries for Bayesian network inference with continuous data

Is there any good libraries that allow me to: Construct a Bayesian network manually Specify the conditional probabilities with any continuous PDF, not just Guassian Perform inference, either exact or ...
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381 views

Are there Machine Learning Models for Networks?

I am working on a regression problem, where the goal is to estimate historic traffic volumes throughout a transportation network. I have traffic counters at 100 locations, so a model can learn the ...
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1answer
115 views

R - Bayesian network for satisfaction survey data

I'm trying to build a bayesian network for satisfcation survey data. My data is made of 13 questions about services, products etc... each customer can answer from 1 (Very unsatisfied) to 4 (very ...
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1answer
49 views

Pecularities of classification of Hidden Markov Models?

Assume that we have set of Hidden Markov Models (Bayesian networks) Set{(n, m, P, A, B)} (n - number of hidden states, m - number of observable states, P - initial probabilities, A - transition matrix,...
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122 views

Good Libraries or Software for Temporal Bayesian Network Structure Learning?

I would like to infer structures of BNs with edges within and between time slices by using data. I tried libpgm (http://pythonhosted.org/libpgm/) and found that 2TBN is ideal for my purpose, but ...
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1answer
1k views

What is difference between Bayesian Networks and Belief Networks?

While reading some articles about Bayesian Networks, I came across many occurrences of Belief Networks. Do both of these terms mean the same thing or is there any difference between Bayesian Networks ...
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1answer
271 views

Understanding Spikeslab Output

I'm using spikeslab for the first time, but don't understand what the output means. It was suggested to me that I use it to tell which variables my dependent variable is most correlated to, in a ...
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1answer
2k views

Bayesian network for classification using PyMc or PyMc3

I am seraching for a while an example on how to use PyMc/PyMc3 to do classification task, but have not found an concludent example regarding on how to do the predicton on a new data ...
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3answers
2k views

Is the direction of edges in a Bayes Network irrelevant?

Today, in a lecture it was claimed that the direction of edges in a Bayes network doesn't really matter. They don't have to represent causality. It is obvious that you cannot switch any single edge ...
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1answer
3k views

What is the difference between a (dynamic) Bayes network and a HMM?

I have read that HMMs, Particle Filters and Kalman filters are special cases of dynamic Bayes networks. However, I only know HMMs and I don't see the difference to dynamic Bayes networks. Could ...
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1answer
192 views

Bayes Classification

In theory we would always like to predict qualitative responses using the Bayes classifier. But for real data, we do not know the conditional distribution of Y given X, and so computing the Bayes ...
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3answers
239 views

For every Bayesian Network, is there a Neural Network that gives the same output?

After thinking about a question comparing Bayesian Network to Neural Network, I am now wondering if they may not be one and the same thing! At this point, my maths (unused for over 20 years fails me!)...
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2answers
235 views

Any case studies using Bayesian Networks for system design trades?

I am exploring using Bayesian Networks to identify the best parameters within a system design, to improve its performance. I'm trying to find any case studies where this has been used successfully or ...