Predicting the Unpredictable
The Magic of Mixture Density Networks Explained
Towards Data Science 11:25 pm on May 21, 2024
Mixture density networks (MDNs) are advanced neural network architectures capable of modeling complex probability distributions by predicting parameters (means, variances, and mixture coefficients) in a Gaussian Mixture Model. They offer accurate predictions with quantifiable uncertainty, useful for scenarios where traditional models fall short, like stock markets or biometrics.
- Mixture Density Networks (MDNs):
- Model complex probabilities:
- Predict Gaussian Mixture Model parameters:
- Handle chaotic scenarios better than linear and non-linear regression models.
- Provide a range of possible futures, capturing uncertainties within predictions.
https://towardsdatascience.com/predicting-the-unpredictable-905f634acc20