Questions tagged [bayesian-networks]
A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG).
bayesian-networks
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Decision tree vs. Naive Bayes classifier [closed]
I am doing some research about different data mining techniques and came across something that I could not figure out.
If any one have any idea that would be great.
In which cases is it better to use ...
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pythonic implementation of Bayesian networks for a specific application
This is why I'm asking this question:
Last year I made some C++ code to compute posterior probabilities for a particular type of model (described by a Bayesian network). The model worked pretty well ...
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What is the difference between a Bayesian network and a naive Bayes classifier?
What is the difference between a Bayesian network and a Naive Bayes classifier? I noticed one is just implemented in Matlab as classify the other has an entire net toolbox.
If you could explain in ...
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Create Bayesian Network and learn parameters with Python3.x [closed]
I'm searching for the most appropriate tool for python3.x on Windows to create a Bayesian Network, learn its parameters from data and perform the inference.
The network structure I want to define ...
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Bayesian spam filtering library for Python
I am looking for a Python library which does Bayesian Spam Filtering. I looked at SpamBayes and OpenBayes, but both seem to be unmaintained (I might be wrong).
Can anyone suggest a good Python (or ...
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What is the difference between causal models and directed graphical models?
What is the difference between causal models and directed graphical models? What is the difference between causal relationships and directed probabilistic relationships? More concretely, what would ...
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Library for Bayesian Networks [closed]
Hello fellow Number crunchers
As the headline suggests, I am looking for a library for learning and inference of Bayesian Networks. I have already found some, but I am hoping for a recommendation.
...
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Learning and using augmented Bayes classifiers in python
I'm trying to use a forest (or tree) augmented Bayes classifier (Original introduction, Learning) in python (preferably python 3, but python 2 would also be acceptable), first learning it (both ...
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Bayesian networks tutorial [closed]
For a beginner, which is the best book to start with for studying Bayesian Networks?
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Bayesian Network with R
I am trying to build a Bayesian network model. However I am unable to install a suitable package. Tried gRain, bnlearn and Rgraphviz for plotting. I have tried in R 2.15 and 3.2
Following are the ...
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Variational Autoencoder gives same output image for every input mnist image when using KL divergence
When not using KL divergence term, the VAE reconstructs mnist images almost perfectly but fails to generate new ones properly when provided with random noise.
When using KL divergence term, the VAE ...
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What is the relationship between bayesian and neural networks?
I'm looking for computationally heavy tasks to implement with CUDA and wonder if neural networks or bayesian networks might apply. This is not my question, though, but rather what the relation between ...
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Bayesian networks in Scala [closed]
I'm looking for a library to create Bayes nets and perform learning and inference on them in Scala (or Java, in case of lack of a better solution). The library should be actively maintained, ...
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Belief Propagation Implementation
I am trying to implement Bayesian Networks.
My main graph is a factor graph that I want to use for belief propagation. But, in belief propagation when calculating messages, not all the arguments are ...
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What does a Bayesian Classifier score represent?
I'm using the ruby classifier gem whose classifications method returns the scores for a given string classified against the trained model.
Is the score a percentage? If so, is the maximum difference ...
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Free Energy Reinforcement Learning Implementation
I've been trying to implement the algorithm described here, and then test it on the "large action task" described in the same paper.
Overview of the algorithm:
In brief, the algorithm uses an RBM of ...
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pymc warning: value is neither numerical nor array with floating-point dtype
I have a Bayes net (DAG) model which I created using pymc 2.3. All the variables in it are Bernoulli random variables.
When I call the MAP.fit() method on it before sampling I get the following ...
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Using bnlearn Function "cpquery" Within a Loop
I'm attempting to use the bnlearn package to calculate conditional probabilities, and I'm running into a problem when the "cpquery" function is used within a loop. I've created an example, shown below,...
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How to model a Bayesian network or, more generally, a directed weighted graph, in SQL?
I found a few articles online providing examples of how to model graphs of various kinds (DAGs, in particular) in SQL, but they all seemed enormously complex, given the relative simplicity of what ...
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Why does Markov blanket contain the children's parents?
I am quite confused about why Markov blanket contains children's parents. Wikipedia says
its children's parents also have to be included, because they can be used to explain away the node in ...
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How to learn a Bayesian Network (structure+parameters) with the WEKA API?
Does anyone know the "proper" procedure to learn a Bayesian Network from data using the WEKA API? I can't find good instructions in the WEKA documentation.
Based on the documentation and what each ...
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Use Google Go's Goroutines To Create A Bayes Network
I have a large dataset of philosophic arguments, each of which connect to other arguments as proof or disproof of a given statement. A root statement can have many proofs and disproofs, each of which ...
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Does scikit-learn have Bayes Net ? If yes is there an implementation for reference
I need to classify the data using BayesNet in Python. I have used scikit learn for other classifiers like Random Forests, SVM etc. I know it has Naive Bayes but I am looking for Bayesian Network alone....
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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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Implement Bayes Net
Is there any c or java example implementing Bayesian Net?
I want to solve some things but Do not where to start?.
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How to use pymc to parameterize a probabilistic graphical model?
How can one use pymc to parameterize a probabilistic graphical model?
Suppose I have a PGM with two nodes X and Y.
Lets say X->Y is the graph.
And X takes two values {0,1}, and
Y also takes two ...
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bnlearn + Rgraphviz: double arrows instead of undirected edges when customizing plots
I am trying to customize a plot of a graph learned with bnlearn using RGraphviz. When I have undirected edges, RGraphviz turns them into directed edges to both directions when I try to customize the ...
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How to increase the size of the text in a Bayesian network plot with bnlearn in R
I am trying to draw a Bsyesian Network in R with bnlearn. Here is the my R code
library(bnlearn)
library(Rgraphviz)
first_variable <- rnorm(100)
second_variable <- rnorm(100)
third_variable &...
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Import WEKA model to MATLAB
Does anyone know how to reuse a WEKA model in MATLAB? I've recently created a Bayes Net model in WEKA, and I want to import that model in MATLAB so I can re-create the Bayesian Network in MATLAB.
...
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AI / Statistical methods for determining the name of a colour
I'm thinking about writing a little library to make a guess at the name of an (RGB value) colour, from a predetermined list of candidates.
My first attempt was based purely on pythagorean distance ...
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Test for conditional independence in python as part of the PC algorithm
I'm implementing the PC algorithm in python. Such algorithm constructs the graphical model of a n-variate gaussian distribution. This graphical model is basically the skeleton of a directed acyclic ...
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Is there a java alternative to the Bayesian Belief Network Framework "Infer.NET"?
Is the are java alternative to Bayesian Belief Network framework - Infer.NET?
Preferable if it be scalable(online learning for large datasets), well-supported(last updated since 2010) and open source ...
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Sample from a Bayesian network in pomegranate
I constructed a Bayesian network using from_samples() in pomegranate. I'm able to get maximally likely predictions from the model using model.predict(). I wanted to know if there is a way to sample ...
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General purpose algorithm for triangulating an undirected graph?
I am playing around with implementing a junction tree algorithm for belief propagation on a Bayesian Network. I'm struggling a bit with triangulating the graph so the junction trees can be formed.
I ...
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Trying to implement a Bayesian neural net with edward
I am trying to apply the Bayesian neural network for non-linear regression presented by Torsten Scholak at PyCon to some real world data and I am getting some weird results. The fit is ok up to a ...
4
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bnlearn::bn.fit difference and calculation of methods "mle" and "bayes"
I try to understand the differences between the two methods bayes and mle in the bn.fit function of the package bnlearn.
I know about the debate between the frequentist and the bayesian approach on ...
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Using c#,c/c++ or java to improve BBN with GA
I have a little problem in my little project , I wish that someone here could help me!
I am planning to use a bayesian network as a decision factor in my game AI and I want to improve the decision ...
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Inference in Gaussian Bayesian Network
I am having some problem related to Partial Abductive Inference in Gaussian Bayesian Networks (Bayesian Networks which accommodates the continuous nature of the random variables and follow jointly a ...
4
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2
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Designing bayesian networks
I have a basic question about Bayesian networks.
Let's assume we have an engine, that with
1/3 probability can stop working.
I'll call this variable ENGINE.
If it stops working, then your car
doesn't ...
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Document Classification using Naive Bayes classifier
I am making a document classifier in mahout using the simple naive bayes algorithm. Currently, 98% of the data(documents) I have is of Class A and only 2% is of class B. My question is, since there is ...
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What is the difference between a Decision Tree and a Bayesian Network?
If I understand it right, both use Bayes Theorem to generate an acyclic graph and calculate percentages based on functions applied at every node.
What is the difference?
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Discrete Bayesian network on Tensorflow Probability, Edward2, and Python
I have a simple Bayesian network:
state
/ \
/ \
V V
signal_1 signal_2
with random variables "state", "signal_1", and "signal_2" with corresponding ...
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Struggling to implement an extremely basic (3 categorical variables) Bayesian network using PYMC3
I'm trying to set up a simplified version of the Bayesian network here with only 3 categorical variables, and then do inference on that. The idea is that D3 is a child of D1 and D2, I'm setting D3=0, ...
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bayesian network learning and inference in R for continuous variables
How can I do bayesian structure learning and inference for continuous variables with R?
I was using the 'bnlearn' package as follows:
For structure learning using the Hill Climbing algorithm , I do ...
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Looking for guidance on multi-part graphical gesture recognition
I'm trying to research existing works in the area of recognizing complex graphical gestures, but struggling to find good search terms or clear documents in the field.
For example, I might want to ...
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Open Source Naïve Bayes Classifier written in Java [closed]
I'm looking for an Open Source Naïve Bayes Classifier library written in Java. Would appreciate any help in finding one.
Is Naïve Bayes Classifier the same as Bayesian Network?
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How can I get unique words from a DataFrame column of strings?
I'm looking for a way to get a list of unique words in a column of strings in a DataFrame.
import pandas as pd
import numpy as np
df = pd.read_csv('FinalStemmedSentimentAnalysisDataset.csv', sep=';',...
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Confusion Matrix of Bayesian Network
I'm trying to understand bayesian network. I have a data file which has 10 attributes, I want to acquire the confusion table of this data table ,I thought I need to calculate tp,fp, fn, tn of all ...
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Visualization of a highly linked graph with neo4j
I'm using Neo4j for a research project and am struggling with a small problem.
The underlying data is a highly linked graph and I'm not able to visualize it in a good manner. As you can see in the ...
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How do I calculate conditional probabilities from data
I'm doing a naive Bayes in Matlab, and it was all good until they said I needed the conditional probabilities. Now I know the formula for conditional p(A|B) = P(A and B)/p(B), but when I have data to ...
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