ToyExample.y_obs: Responses used in training part for 1D toy problem

In mgoulet847/tagi: Tractable Approximate Gaussian Inference in Neural Networks

Description

The orignal dataset represents a 1D regression problem from Hernández-Lobato & Adams (2015): y = x^{3} + ε where ε \sim \mathcal{N}(0,9) and x \in [\,-4,4]\,. In this dataset, x and y are normalized.

Usage

ToyExample.y_obs

Format

A data frame with 20 rows and 1 variable y

Details

The dataset generated with the seed from the TAGI repository was used for comparison purposes.

Source

https://github.com/CivML-PolyMtl/TAGI/blob/master/ToyExample/ToyExample_1D.m

References

Hernández-Lobato, J. M., & Adams, R. "Probabilistic backpropagation for scalable learning of bayesian neural networks." International Conference on Machine Learning. 2015.

mgoulet847/tagi documentation built on Dec. 21, 2021, 5:10 p.m.