Questions tagged [graphical-model]
The graphical-model tag has no usage guidance.
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Graph Clustering algorithms when both nodes *and* edges have features (numerical, categorical and potentially even temporal!)
I'm trying to figure out how much complexity I can get away with and am looking for model recommendations.
I have transactional data on hand - the features being customer id, customer balance, ...
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How to Use Graph Learning Libraries to Predict Edges on a Graph where Each Node Has an Embedding?
An undirectional graph $\mathcal{G}$ has the set of nodes $\mathcal{N}$ where each node has an associated unique embedding of $512$ dimensions. Note that the embeddings themselves are fixed, and not ...
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For a node in an undirected graph - does the node affect itself if its markov blanket is known?
Consider the following Markov Random Field.
Question 1: Which of the following nodes will have no effect on H given the Markov Blanket of H?
Question 2: Will node H itself have any effect on itself, ...
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Is the node in undirected graph itself included in the set of its own Markov Blanket?
Consider an undirected graph with nodes set {a,b,c,d,e}, and edge set {(a,b), (a,c), (a,d), (a,e)}.
From the above info, you will clearly visualise that the node a ...
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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-...
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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 ...
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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 ...
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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;
...
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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 ...
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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 ...
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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.
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How can spatiotemporal population data be used for modeling migration?
I have a dataset that contains the population of butterflies(5 species) for 15 years for different locations. I want to model it against the climate index collected for same time period and location. ...
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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....
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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 ...
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How to interpret a trained Decision Tree [closed]
I built my first decision tree, to predict if students will pass or not - the data set - depending on 30 variables. Now I need to know how to read the decision tree, since many variables were strings ...
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Training a Graph model like an Artificial Neural Network
I currently have a Graph model whereby I am mapping connections of different types between entities and attributing a weight to these connections based upon my own personal experience. Also, I would ...
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Graph to display differences (or lack of) in multilevel categorical data
I am trying to find an interesting way to interpret and display a set of data for the research I'm working on. Columns 2-4 show the net change from time 1 to time 2 in antibiotic coverage for ...
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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 ...
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Intuitive explanation of how Latent SVM works?
Can anyone explain (or refer to a great explanation of) the intuition of how Latent SVM works?
I think Latent SVM should have some resemblance to CRF (Conditional Random Fields) and EM (expectation ...
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System to provide guide to students about getting admissions to universities of their choice or some specific courses [closed]
I basically want to build a system which will provide a student step by step guide or you can say a full route about what courses he/she should take currently or what examinations they need to clear ...
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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 ...
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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 ...
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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 ...
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Can I use manifold learning to transform the feature set as a substitute of graph kernel of SVC
I just wonder since the manifold learning under scikit-learn has component of graph-based transformation (e.g. Shortest-path graph search under Isomap) I can then transform the feature data set (i.e. ...
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Handling time series data with gaps
I am working on a dataset with physical measurements taken daily (weight, bmi, etc...) and I am working through the process to graphically represent it. I think it is worth noting that every day has a ...
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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 ...
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How to approach graphed data for a binary classification system?
I'm looking for articles and other reading material on handling and modeling graph-shaped data for classification systems. As I've never working with graphed base machine learning anything from novice ...
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Graphs demonstrating the structure of neural networks are very unclear
This image looks pretty familiar to anyone getting acquainted with neural networks, and on first glance it makes a lot of intuitive sense.
But on second, third, fourth, etc glance, some questions ...
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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 ...
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