I'm trying to use a distribution from tensorflow_probability to define a custom loss function in Keras. More specifically, I'm trying to build a Mixture Density Network. My model works on a toy dat...

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 ...

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 depen...

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)...

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 bo...

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, plea...

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(2...

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 resul...