random forest

Why Use Random Forest in Histology?

There are several reasons why random forest is particularly useful in histology:
- Accuracy: Random forest tends to provide high accuracy in classification tasks due to its ensemble nature.
- Robustness: The algorithm is less likely to overfit compared to other models, making it reliable for varied and complex histological data.
- Interpretability: While individual trees may be complex, the overall model can provide insights into which features are most important for classification.
- Scalability: Random forest can handle large datasets effectively, which is common in histological studies.

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