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Timeline for When to use Gaussian mixture model?

Current License: CC BY-SA 3.0

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May 4, 2018 at 18:17 review Suggested edits
May 4, 2018 at 19:04
Dec 17, 2017 at 20:23 answer added mynameisvinn timeline score: 0
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Feb 6, 2017 at 5:20 comment added Vinay @arpit-sisodia, Link you have provided suggests more of trial and error method to see if GMM fits to my data. Is there a conclusive way/Thumb rule to decide up on the models to use. Trial-and-error method of playing with more mixtures can fit my data. But is there a certain way of deciding up on? Like we need to have Linear separability of data for SVM classification
Feb 6, 2017 at 5:20 comment added Vinay @arpit-sisodia, We are working on feasibility of a hardware keyboard setup which seem to have specific features and we are planning to model it using GMM. We dont know the underlying process clearly and hence we are trying to model using machine learning methods. So, we are not sure if there is actually a mixture of gaussians in the underlying process. Moreover, it is multi-dimensional and we cannot visualize it to see if it is mixture of gaussians
Feb 6, 2017 at 1:52 history tweeted twitter.com/StackStats/status/828421080436072450
Feb 5, 2017 at 18:12 comment added gung - Reinstate Monica You can think of it as a form of clustering where you don't have labeled data & believe the latent groupings are perfectly multivariate normal.
Feb 5, 2017 at 18:08 comment added Arpit Sisodia what is ur data set and what is your exact problem? It's used when data follows ( is a mixture of) more than 1 normal distribution. See another question -stats.stackexchange.com/questions/236295/…
Feb 5, 2017 at 18:00 answer added Slayer timeline score: 4
Feb 5, 2017 at 17:50 history edited Franck Dernoncourt CC BY-SA 3.0
edited tags; edited title
Feb 5, 2017 at 17:49 review First posts
Feb 5, 2017 at 18:12
Feb 5, 2017 at 17:47 history asked Vinay CC BY-SA 3.0