ArticleJournal of cheminformatics2024
Be aware of overfitting by hyperparameter optimization!
Article in Journal of cheminformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
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- Hybrid machine learning and Gaussian process for antenna parameter estimation.Scientific reports · 2026Article
- Machine Learning Prediction of Analyte-Induced Fluorescence Perturbations in DNA-Functionalized Carbon Nanotubes.Nano letters · 2026Article
- A Machine Learning Model for Predicting Recurrent Pregnancy Loss: Retrospective Integration of Routine Serum IL-33, C-Reactive Protein, and Lymphocyte Subset Counts.International journal of general medicine · 2026Article
- Early Sound-Based Meal Onset Detection Using Hidden Markov Models (HMMs).IEEE journal of translational engineering in health and medicine · 2026Article
- HMDF-Net: a transfer learning-based heterogeneous multimodal dynamic fusion network for depression detection among inmates in correctional facilities.Frontiers in psychiatry · 2026Article
- Comparative Chemical Space Analysis of Pesticides and Substances with Genotoxicity Data.Chemical research in toxicology · 2025Article
- A Three-Module Machine Learning Framework for Protein Sequence- and Temperature-DependentACS synthetic biology · 2025Article
- Development of a Large-Scale Dataset of Chest Computed Tomography Reports in Japanese and a High-Performance Finding Classification Model: Dataset Development and Validation Study.JMIR medical informatics · 2025Article
- Advanced machine learning for innovative drug discovery.Journal of cheminformatics · 2025Article
- UMAP-based clustering split for rigorous evaluation of AI models for virtual screening on cancer cell lines.Journal of cheminformatics · 2025Article
- Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World.Chemical research in toxicology · 2025Review
- Generalizable, fast, and accurate DeepQSPR with fastprop.Journal of cheminformatics · 2025Article
- AttenhERG: a reliable and interpretable graph neural network framework for predicting hERG channel blockers.Journal of cheminformatics · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Hyperparameter optimization is very frequently employed in machine learning. However, an optimization of a large space of parameters could result in overfitting of models. In recent studies on solubility prediction the authors collected seven thermodynamic and kinetic solubility datasets from different data sources. They used state-of-the-art graph-based methods and compared models developed for each dataset using different data cleaning protocols and hyperparameter optimization. In our study we showed that hyperparameter optimization did not always result in better models, possibly due to overfitting when using the same statistical measures. Similar results could be calculated using pre-set hyperparameters, reducing the computational effort by around 10,000 times. We also extended the previous analysis by adding a representation learning method based on Natural Language Processing of smiles called Transformer CNN. We show that across all analyzed sets using exactly the same protocol, Transformer CNN provided better results than graph-based methods for 26 out of 28 pairwise comparisons by using only a tiny fraction of time as compared to other methods. Last but not least we stressed the importance of comparing calculation results using exactly the same statistical measures.Scientific Contribution We showed that models with pre-optimized hyperparameters can suffer from overfitting and that using pre-set hyperparameters yields similar performances but four orders faster. Transformer CNN provided significantly higher accuracy compared to other investigated methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.