Simple Methods for Initializing the EM Algorithm for Gaussian Mixture Models

@article{Blmer2013SimpleMF,
  title={Simple Methods for Initializing the EM Algorithm for Gaussian Mixture Models},
  author={Johannes Bl{\"o}mer and Kathrin Bujna},
  journal={CoRR},
  year={2013},
  volume={abs/1312.5946}
}
An improved version of this paper (Adaptive Seeding for Gaussian Mixture Models) has been accepted for publication in the Proceedings of the 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2016 and is available via the DOI 10.1007/978-3-319-31750-2 24. Abstract—In this paper, we consider simple and fast approaches to initialize the Expectation-Maximization algorithm (EM) for multivariate Gaussian mixture models. We present new initialization methods based on the well… CONTINUE READING