The Latent Bernoulli-Gauss Model for Data Analysis
Disciplines
Text
English
ID: <
10670/1.hozt7k>
We present a new latent-variable model employing a Gaussian mixture integrated with a feature selection procedure (the Bernoulli part of the model) which together form a "Latent Bernoulli-Gauss" distribution. The model is applied to MAP estimation, clustering, feature selection and collaborative filtering and fares favorably with the state-of-the-art latent-variable models.