Questions tagged [graphical-model]

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0answers
42 views

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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0answers
28 views

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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2answers
211 views

Why does a belief network need to be represented using a directed acyclic graph (DAG)?

I would have thought that it's because DAGs preserve the dependency relationships between the variables, but I am currently unsure. Thanks
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0answers
34 views

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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0answers
65 views

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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0answers
12 views

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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0answers
212 views

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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1answer
133 views

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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2answers
39 views

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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1answer
544 views

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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0answers
53 views

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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1answer
49 views

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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0answers
41 views

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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1answer
156 views

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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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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0answers
46 views

Measuring connectivity between clusters in an organizational network in R

I'm trying to conceptualize a network analysis problem and figure out where to start in terms of analysis techniques in R. Apologies as I'm fairly new to all this. Basically, I have a employee ...
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0answers
86 views

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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1answer
738 views

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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0answers
447 views

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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1answer
198 views

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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1answer
80 views

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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3answers
598 views

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 ...