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Questions tagged [mixture-model]

In statistics, a mixture model is a probabilistic model that is formed by a combination of probabilistic models. For example, the Gaussian mixture model is the weighted sum of Gaussian distributions. Mixture models are mainly used in probabilistic clustering of data and modelling of unknown distributional shapes.

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Understanding concept of Gaussian Mixture Models

I'm trying to understand GMM by reading the sources available online. I have achieved clustering using K-Means and was seeing how GMM would compare to K-means. Here is what I have understood, please let me know if my concept is wrong: GMM is like…
StuckInPhDNoMore
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Effect of feature scaling on accuracy

I am working on image classification using Gaussian Mixture Models. I have around 34,000 features, belonging to three classes, all lying in a 23 dimensional space. I performed feature scaling on both the training and testing data using different…
pseudomonas
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Gaussian Mixture Models of an Image's Histogram

I am attempting to do automatic image segmentation of the different regions of a 2D MR image based on pixel intensity values. The first step is implementing a Gaussian Mixture Model on the image's histogram. I need to plot the resulting gaussian…
DottedGlass
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Simulate mixture data with different mix dependecies structure between each two variables?

I would like to simulate a mixture data, say 3 dimensional data. I would like to have 2 different components between each two variables. That is, simulate mixture data (V1 and V2) where the dependencies between them is two different normal…
user7905871
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How to model a mixture of 3 Normals in PyMC?

There is a question on CrossValidated on how to use PyMC to fit two Normal distributions to data. The answer of Cam.Davidson.Pilon was to use a Bernoulli distribution to assign data to one of the two Normals: size = 10 p = Uniform( "p", 0 , 1) #this…
Michael Schubert
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Any suggestions for how I can plot mixEM type data using ggplot2

I have a sample of 1m records obtained from my original data. (For your reference, you may use this dummy data that may generate approximately similar distribution b <- data.frame(matrix(rnorm(2000000, mean=c(8,17), sd=2))) c <- b[sample(nrow(b),…
rk567
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scikit-learn GMM produce positive log probability

I am using Gaussian Mixture Model from python scikit-learn package to train my dataset , however , I fount that when I code -- G=mixture.GMM(...) -- G.fit(...) -- G.score(sum feature) the resulting log probability is positive real number... why is…
Jing
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predict_proba is not working for my gaussian mixture model (sklearn, python)

Running Python 3.7.3 I have made a simple GMM and fit it to some data. Using the predict_proba method, the returns are 1's and 0's, instead of probabilities for the input belonging to each gaussian. I initially tried this on a bigger data set and…
Dave
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R : function to generate a mixture distribution

I need to generate samples from a mixed distribution 40% samples come from Gaussian(mean=2,sd=8) 20% samples come from Cauchy(location=25,scale=2) 40% samples come from Gaussian(mean = 10, sd=6) To do this, i wrote the following function : dmix…
Raaj
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Mixture of Gaussian and Gamma distribution

I'm looking for some script/package in R (Python will do too) to find out the component distribution parameters from a mixture of Gaussian and Gamma distributions. I've so far used the R package "mixtools" to model the data as mixture of Gaussians,…
The August
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C++ Implementation of GMM using Gibbs Sampler i.e Dirichlet Process Gaussian Mixture Model

I am looking a C++ implementation of a multi-variate GMM that uses a Gibbs Sampling based approach to fitting / classification (rather than the usual EM based), in order to be able to make full use of a priori information and add in constraints.…
oracle3001
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How can I write GMM (Gaussian Mixture Model) in Java?

How can I write a GMM (Gaussian mixture model) in Java? There are some implementations in MATLAB, but I am looking for some documentation about it and example code in Java. PS: If it is possible, how can I adopt the Weka implementation in my…
kamaci
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Accounting for noise in 2D Gaussian model

I need to fit a 2D gaussian embedded into substantial uniform noise, as shown in the left plot below. I tried using sklearn.mixture.GaussianMixture with two components (code at the bottom), but this obviously fails as shown in the right plot…
Gabriel
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Mixture of poisson distribution using flexmix in R

I am trying to fit mixture of 3 poisson distribution using flexmix package in R as per the code below: require(flexmix) freq<- c(222950,111682,72429,48126,34515,25801,19199,15033,11859, 9226, 7363, 5910, 4659, 3723, 2985, 2291,1907, 1447,…
tamal kuila
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DP-GMM and online cluster assignment

I expected scikit-learn's DP-GMM to allow for online update of cluster assignments given new data, but sklearn's implementation of DP-GMM only has a fit method. My understanding of variational inference is yet unclear and I think that the inability…
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