Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification

Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification

Applied datasets can vary from a few hundred to thousands of samples in typical quantitative structure-activity/property (QSAR/QSPR) relationships and classification. However, the size of the datasets and the train/test split ratios can greatly affect the outcome of the models, and thus the classifi...

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Bibliographic Details
Main Authors: Anita Rácz, Dávid Bajusz, Károly Héberger
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Molecules
Subjects:
machine learning
XGBoost
validation
training/test split ratio
multiclass classification
imbalanced
Online Access:https://www.mdpi.com/1420-3049/26/4/1111

Internet

https://www.mdpi.com/1420-3049/26/4/1111

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