Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [graphical-model]

28 questions
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3 answers

Which tribe does Probabilistic Graphical Models fall under?

Pedro Domingos in "The Master Algorithm" listed five tribes of machine learning algorithms: Symbolists Connectionists Evolutionaries Bayesians Analogizers Which category do probabilistic graphical models fall under? From wikipedia…
alvas
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Viterbi-like algorithm suggesting top-N probable state sequences implementation

Traditional Viterbi algorithm (say, for hidden Markov models) provides the most probable hidden state sequence given a sequence of observations. There probably is an algorithm for decoding top-N probable hidden states sequences (k-shortest paths or…
Anton
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Why does a belief network need to be represented using a directed acyclic graph (DAG)?

I would have thought that it was because DAGs preserve the dependency relationships between the variables, but I am currently unsure.
silverscientist
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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 approximate I looked at the following libraries…
Zebra Propulsion Lab
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How to visualize optimization problems' feasible region?

Is there any tool to visualize the feasible region when given a set of Linear equations (equalities and inequalities). If not, can anyone suggest a way to visualize it? If I am going to do it myself using Python, which libraries should I use. I have…
Mina Ashraf
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Problems with Graphical Lasso

I'm trying to use the Graphical Lasso algorithm (more specifically the R package glasso) to find an estimated graph representing the connections between a set of nodes by estimating a precision matrix. I have a feature matrix containing the values…
F Lourenço
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Node values in Boltzmann machines (0/1 vs -1/1). Are they the same?

Boltzmann machines were introduced by Hinton and Sejnowski as taking values in $\{0,1\}$. The Wikipedia entry also uses this convention. However, Hopfield Networks, which are the deterministic version of Boltzmann machines, are usually introduced as…
samlaf
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What is the best algorithm for deterministic belief propagation?

Here is a simple example: In a 3D space, if point A is the geocenter of a planet, point B is its north pole, and point C has a fixed latitude/longitude on the planet surface. Then the position of point C can be inferred from the position of A and B…
tribbloid
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Learning with dirichlet prior - probabilistic graphical models exercise

I have the following problem: Suppose we are interested in estimating the distribution over the English letters. We assume an alphabet that consists of 26 letters and the space symbol, and we ignore all other punctuation and the upper/lower case…
bouritosse
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Implement gaussian mixture model with stochastic variational inference

I am trying to implement Gaussian Mixture model with stochastic variational inference, following this paper. This is the pgm of Gaussian Mixture. According to the paper, the full algorithm of stochastic variational inference is: And I am still…
user5779223
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Understanding the plate notation for gaussian mixture models and latent dirichlet allocation

I am having troubles understanding the plate notation being used in LDA and GMM. In specific the class-variable deciding which parameters that generates the observation in GMM's and the topic-assignment in LDA's. Why does it not have a an edge…
richard
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Where do the "semantics" of a Bayesian network come from?

On Bayesian Networks, Ghahramani (2001) says: A node is independent of its non-descendants given its parents. This point is fundamental enough that Ghahramani calls it the “semantics” of a Bayesian network. It is certainly useful, and it is…
ashman
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How to perform link prediction in text based relationship data

I need to establish if there is a link between 2 columns from two different datasets with one matching column, where; Dataset1: bipartite: (M, DS) M G m23 ds3 m23 ds67 m54 ds325 ... ... Dataset2: tripartite: (M, G, DG) M G …
namhsuya
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Dependency Graph

I want to create a dependency graph of some sensors in the network ( based on their reported value). Please note that a change in the values of sensors is related to each other. For example, if the measured value by a sensor increases, it is…
Arkan
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How to interpret the graph representing the fit provided by the ARIMA model?

I'm following this tutorial here to build an ARIMA model in R. I've done a Forecast using a fitted model in R. I specified the forecast horizon h periods ahead for predictions to be made and used the fitted model to generate those predictions. Then…
ilni
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