⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

February 26, 2024ACS OmegaOpen Access

Evaluation and Optimization Methods for Applicability Domain Methods and Their Hyperparameters, Considering the Prediction Performance of Machine Learning Models

Hiromasa Kaneko

View Full Paper

Ask AI

Bookmark

Share

Abstract

In molecular, material, and process design and control, the applicability domain (AD) of a mathematical model

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Hiromasa Kaneko (2024) studied this question.

synapsesocial.com/papers/68e777b3b6db6435876ecd38 https://doi.org/10.1021/acsomega.3c08036

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1A quantitative evaluation method for the applicability domain of aerodynamic/aerothermal machine learning prediction modelsOriginal Research · 2026
2Expanding the Applicability Domain of Machine Learning Model for Advancements in Electrochemical Material Discovery2024 · 4 citations
3Chemoinformatic regression methods and their applicability domain2024 · 26 citations
4Determining Domain of Machine Learning Models using Kernel Density Estimates: Applications in Materials Property Prediction2024 · 2 citations
5Synthetic Applicability Domain (SynAD): Navigating Chemical Space for Reliable AI‐Driven Reaction PredictionOriginal Research · 2026