Oct 7, 2022 · This work provides the network design choices and inferential methods for creating better performing PIs with ANNs.

Mar 24, 2022 · Constructing Prediction Intervals with Neural Networks: An Empirical. Evaluation of Bootstrapping and Conformal Inference Methods. Contarino ...

This work provides the network design choices and inferential methods for creating better performing PIs with ANNs. A two-step experiment is executed across 11 ...

Artificial neural networks (ANNs) are popular tools for accomplishing many machine learning tasks, including predicting continuous outcomes.

This brief proposes an efficient technique for the construction of optimized prediction intervals (PIs) by using the bootstrap technique.

Artificial neural networks (ANNs) are popular tools for accomplishing many machine learning tasks, including predicting continuous outcomes.

Constructing Prediction Intervals with Neural Networks: An Empirical Evaluation of Bootstrapping and Conformal Inference Methods.

This paper tries to shed new light on how prediction intervals can be constructed, using methods such as normalized and Mondrian conformal prediction, in such a ...

Constructing Prediction Intervals with Neural Networks: An Empirical Evaluation of Bootstrapping and Conformal Inference Methods by Alex Contarino ...

Constructing Prediction Intervals with Neural Networks: An Empirical Evaluation of Bootstrapping and Conformal Inference Methods · Computer Science, Mathematics.