Add noise to the dataset to the existing clean dataset. Train your models with both clean and noisy dataset.
Plot learning curves (training vs. validation score) to analyze whether models are overfitting or underfitting in both scenarios.
Compute and visualize per-class F1-scores to understand how noise impacts each class differently.
Add noise to the dataset to the existing clean dataset. Train your models with both clean and noisy dataset.
Plot learning curves (training vs. validation score) to analyze whether models are overfitting or underfitting in both scenarios.
Compute and visualize per-class F1-scores to understand how noise impacts each class differently.