Discover effective strategies to enhance underperforming image classification models. Explore data quality, augmentation, architecture adjustments, and more for improved accuracy!
Table of Contents
Question
You train an image classification model that achieves less than satisfactory evaluation metrics. How might you improve it?
Answer
Add more images to the training set.
Explanation
To enhance an underperforming image classification model, consider these steps:
- Data Quality: Ensure a diverse and balanced dataset, minimizing biases and ensuring representative samples.
- Augmentation: Expand the dataset by augmenting images, introducing variations like rotations, flips, or color changes.
- Model Architecture: Experiment with different architectures, adjusting layers, or using pre-trained models for feature extraction.
- Hyperparameters: Tweak parameters like learning rate, batch size, or optimizer to optimize model performance.
- Regularization: Apply techniques like dropout or weight regularization to prevent overfitting.
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