fig11

A new framework for predicting tensile stress of natural rubber based on data augmentation and molecular dynamics simulation data

Figure 11. Comparative analysis of R2 values across multiple algorithms for diverse models. NNI-SMOTE: Nearest Neighbor Interpolation-Synthetic Minority Oversampling Technique; GMM-VSG: a Virtual Sample Generation algorithm based on Gaussian Mixture Models; VAE: Variational Autoencoder; VSG: Virtual Sample Generation; OK: Ordinary Kriging; GBR: Gradient Boosting Regression; SVR: Support Vector Regression; LASSO: Least Absolute Shrinkage and Selection Operator; ANN: Artificial Neural Networks; BRR: Bayesian Ridge Regression.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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