We describe an approach to regression based on building a probabilistic model with the aid of visualization. The “stereopsis” data set in the predictive uncertainty challenge is used as a case study, for which we constructed a mixture of neural network experts model. We describe both the ideal Bayesian approach and computational shortcuts required to obtain timely results.
- Markov Chain Monte Carlo
- Loss Function
- Input Space
- Predictive Distribution
- Markov Chain Monte Carlo Method
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.