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# Questions tagged [gaussian-mixture]

A type of mixed distribution or model which assumes subpopulations follow Gaussian distributions.

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### Skewness of fitted mixture not correct?

I fitted a gaussian mixture to my financial data. The values are: $\pi= 0.3$ $\mu_1= -0.01$ $\mu_2= 0.01$ $\sigma_1=0.01$ $\sigma_2=0.03$ One can see, that both single distributions have a ...
1k views

### Comparing K-Means and Expectation Maximization on the dataset generated - When does K-Means perform better?

I was experimenting with K-Means and Gaussian Mixture Models (Expectation-Maximization) on the data set that I generated. Here is how the plot for two distributions looks like: Since this was ...
1k views

### Mixed data in Gaussian Mixture Models

Is it possible to use a dataset with mixed variables such as continuous, ordered, and categorical variables and cluster the data using the Gaussian Mixed Model with EM algorithm. I cannot find ...
70 views

### How to use Bayes' Theorem to detect an event in a noisy signal

I'm trying to use Bayes' Theorem to solve a question that's come up in work, but I don't know if I've done it correctly, because the result seems a bit strange. The problem involves a stochastic ...
3k views

### The number of parameters in Gaussian mixture model

I have D-dimensional data with K components. How many parameters if I use a model with full covariance matrices? and How many if I use diaogonal covariance matrices?
607 views

### How to do batch learning for Gaussian Mixture Models?

I have a huge dataset of features on which I want to fit a Gaussian Mixture Model using standard expectation maximization, as it is implemented by sklearn. Since not all features fit into the memory ...
336 views

### Bimodal univariate distributions are always indicative of a mixture of two random variables. Is this correct? [duplicate]

Say I see a bimodal distribution like this (with the domain, or random variable, $Z$): Does that instantly mean that I am seeing not a distribution of one independent random variable $Z$, but ...
96 views

### What does 'vector-valued' mean?

What is the difference of a feature vector and a 'vector-valued observation' as described here? The term 'vector-valued' is used in the following context: "Most state-of-the-art [Automatic Speech ...
158 views

### Mixture Model Distributions

I wonder, if there could be a Pareto Mixture Model, just like the Gaussian Mixture Model (GMM). How am I supposed to build a Pareto Mixture Model (PMM)?
117 views

### I want to show a local optimum in my paper, how do I generate the data for it?

I'm writing a paper where I am explaining the problems of local optimum in my clustering algorithm. While clustering, in my data I would at times get local optimums. But I've tried and I cannot ...
565 views

### My MCMC do not overlap : Mixturemodel with JAGS and R

I fitted a JAGS model and I have those results : My questions are: Why do my chains not overlap, and how can I fix that? I used the following method: My model is a mixture Gaussian model of two ...
223 views

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### How to know if my Gaussian mixture model has enough training data?

A somewhat soft question - I'm training a Gaussian mixture model (with the EM algorithm) on data of size $N$ ($N$ is typically between 4 and 64). How much samples do I need? obviously it depends on ...
152 views

### How to project data onto a model (specifically, GMM)?

I'm using data to train a Gaussian mixture model (GMM). I then take a sample and would like to see its projection on the GMM 'space'. I can think of an optimization problem such as this: consider $y$ ...
1k views

### How do I “split” Gaussian mixture components when training EM/GMM based classifier?

In order to improve performance of my Gaussian Mixture Model based classifier, I was recommended to start with a single multivariate Gaussian, estimate its parameters, and "split" it into two mixtures,...
208 views

### Mixture Model with dependant observations

I am trying to model a process in which each datapoint is generated sequentially, so the current observation depends on the last one. Some example data could look like, ...
306 views

### Finding out if your data belongs to normal distribution

Is there a way to find out if your data belongs to one or more (mixture) normal distributions? I probably could calculate what is the standard deviation of my data, but I'm not sure what else to do ...
3k views

### Testing for Unimodality or Bimodality Data Using MATLAB

I am trying to figure out what I did wrong or what I could do to get accurate results. I have n vectors of data, and I am trying to decide whether each dataset is unimodal or bimodal. I assumed that ...
47 views

### What is a mixing process?

What does this mean? Asset prices follow a mixture of normal distributions with a mixing process dependent on the unobservable information arrival process.
43 views

### Using AIC/BIC within cross-validation for likelihood based loss functions

For a course I am teaching, I am having my students fit a Gaussian mixture model using MLEs via the EM algorithm to a bivariate dataset. I have asked the students to use use cross-validation to choose ...
1k views

### Understanding the log-likelihood (score) in scikit-learn GMM

I have been training a GMM (Gaussian Mixture, clustering / unsupervised) on two version of the same dataset: one training with all its features and one training after a PCA truncated to its 2 first ...
19 views

### How to use GMMs for acoustic signal classification?

There are a number of applications of the Gaussian Mixture Model (GMMs) to acoustics/audio data for the purposes of classification; ex paper1 and ex paper2. GMMs ...
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### Generate data points for a Gaussian with drawing probability

I am trying to solve this question: Generate 500 data points drawn from each of 3 (three) Gaussians: $N_1(1, 0.1)$, $N_2(1.5., 0.1)$ and $N_3(2, 0.2)$ whose drawing probability on each iteration ...
748 views

### How can I find mean and covariance after EM iteration on GMM algorithmm?

I have a dataset divided in 2 class(lets call x1,x2) but I don't know their mean and covariance. For each class I looked their graph and made a guess about their sub-classes, then run an EM(...
604 views

### Understanding hidden markov model, and how it is applied in speech recognition

I have for some some time tried to understand how this hidden markov model (hmm) works, and have found a lot of tutorials/papers on it which make use of the same examples/principles of explaining the ...
150 views

### Learn parameters for truncated Gaussian

I would like to learn the parameters for a truncated gaussian like this one. I'm using this formula for the probability density \$f(x | \mu, \sigma^2) = \exp\left(-\frac{(x-\mu)^2}{2\sigma^2}\right) \...
38 views

### what is the difference in training and testing for Gaussian and Mixture of Gaussians

what is the difference in training and testing between the Gaussian and Mixture of Gaussians? Are they the same except one is unimodal and one is multimodal?
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### Decomposition of multimodal distributions

I have decomposed a multimodal distribution into the constituent single distributions for for further analysis. I have spent some time researching various approaches and I have not found one that that ...
219 views

### QDA vs EM with Gaussian likelihoods

QDA (quadratic discriminant analysis) assumes that the K different classes are generated by K different multivariate Gaussians, each with potentially different mean vector and covariance matrix. If ...