The ‘TreeBagger’ class in MATLAB does not natively support incremental learning, which means you can't directly update an existing model with new data subsets.
You can try the following methods for efficient memory usage:
Train Multiple Models on Data Subsets:
- Divide your dataset carefully so that it’s not biased
- Train on each chunk
- Combine models by averaging all the predictions
Preprocess data:
Consider down sampling or preprocessing your data before training. Feature selection, dimensionality reduction (e.g., PCA), or using a smaller, more representative subset of the data helps reduce the memory footprint.
Alternative algorithms:
If the above methods don’t work you can consider using other machine learning algorithms like XGBoost and LightGBM that can handle large datasets efficiently.
Hope this helps!
