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Questions - expectation-maximization

Singular Covariance Matrix in Expectation Maximization

I was trying to code up an EM algorithm in python for clustering images of different types. My understanding of the EM algorithm is as follows: Accordingly, I coded the same in python. Here's my code...

Hara

python

gmm

expectation-maximization

Votes: 0

Answers: 1

Latest Answer

To prevent the covariance matrix from becoming singular, you could add an arbitrary value along the diagonal of the matrix, i.e. val * np.identity(size) as this ensures that the covariance matrix wil...

Chris

Pgmpy: expectation maximization for bayesian networks parameter learning with missing data

I'm trying to use the PGMPY package for python to learn the parameters of a bayesian network. If I understand expectation maximization correctly, it should be able to deal with missing values. I am cu...

TdV

python

missing-data

bayesian-networks

expectation-maximization

pgmpy

Votes: 0

Answers: 1

Latest Answer

Since there is still no answer to your specific question, let me propose a solution with another module: #import import pandas as pd import numpy as np import pyAgrum as gum # Read data that does no...

Pierre-Henri Wuillemin

Expectation Maximization using a Poisson likelihood function

I am trying to apply the expectation-maximization algorithm to estimate missing count data but all the packages in R, such as missMethods, assume a multivariate Gaussian distribution. How would I appl...

Constantin

r

expectation-maximization

Votes: 0

Answers: 1

Latest Answer

Defining x0: x0 <- x[!is.na(x)] The Jeffreys/reference prior for a Poisson distribution with mean lambda is 1/sqrt(lambda). From the observed values, this results in lambda having a gamma referenc...

jblood94

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