# Questions tagged [bayesian-networks]

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24 views

### Learning the uncertainty of a ML algorithm

I have a regression GAM (General Additive Model) and I want to learn its epistemic uncertainty( the variance of my residuals or predictions as a function of my input). I have already used a bayesian ...
7 views

### How does the weights-per-row and inertia impact node-level probability in Pomegranate Bayesian Networks?

I am using the pomegranate python package to create a Bayesian N/w from a dataset I have using from_samples(). I want to give more weightage to some rows using the weights =[] option in the .fit() ...
23 views

### Hyperparameter tuning of neural networks using Bayesian Optimization

One of the assumptions for finding good hyperparameters using Bayesian optimization (GP) is that the unknown function is smooth. Is this assumption valid for neural networks or at least for most of ...
8 views

### what does “Tree” refer to in Tree-structured Parzen Estimators

I am going through the literature of Hyperparameter optimization techniques and came across TPE. There is very little to no explanation on why the name has "Tree" in it. What is Tree referring to? and ...
28 views

### Bayesian Network - a practical example of marginal probability calculation?

I was watching an online course on the topic Bayesian Networks and I have a question regarding the calculation of marginal probabilities. Hier is the given network: and the corresponding course video ...
10 views

### How to draw a Bayes Network (DAG) when the structure and probabilities are unknown … to be learnt from the data

I need some help and resources to understand how to draw DAG (Bayesian Networks) by learning the structure and probabilities from the data. Thanking you.
35 views

### How to tune the hyperparameters of XGBoost and RF? [closed]

How to tune the hyperparameters of XGBoost and RF in python? There are several methods to tune hyperparameteres of XGBoost and RF such as Bayesian Optimization and meta learning and gridseachcv? ...
267 views

### can't install gRain package

I am new to R and trying to install the gRain package. However, I am getting the error: dependency āgRbaseā is not available Then, when trying to install gRbase ...
54 views

### 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 ...
15 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 ...
22 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 ...
126 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 ...
47 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 ...
101 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 ...
37 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 ...
732 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 ...
16 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 ...
46 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 ...
385 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?...
850 views

### Undestanding Bayesian network with OpenMarkov

I downloaded OpenMarkov software for probabilistic graphical models and tried it on mtcars dataset. The ...
354 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 ...
7k 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 ...
48 views

### Probability of event given two depandant events [closed]

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?
147 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 / ...
84 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 ...
62 views

### Training with feature metadata - bayesian network (naive bayes) [closed]

I am building a project for fun - reverse astrology! I am making a dataset like: ...
44 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. ...
19 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, ...
2k 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 ...
93 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 ...
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. ...
133 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 ...
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 ...
384 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 ...
136 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 ...
51 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,...
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 ...
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 ...
293 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 ...
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 ...
3k 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 ...
4k 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 ...
219 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 ...