Our analysis revealed that Random Forest consistently outperformed other models in balancing predictive accuracy and alignment with financial forecasts. Among the tested configurations, the ...

The model employs the Random Forest Algorithm to provide robust and interpretable predictions. Project Overview. Title: Stroke Prediction Using Random Forest; Course: Machine Learning (IF540-L) ...

Diabetes Data Set. Contribute to IvanDJ125/decision-tree---random-forest---boosting-algorithms-project development by creating an account on GitHub.

This method is avoided for the lung cancer dataset from Kaggle, and a fragmented model is used to undermine the model's performance. It is seen that among the combinations, the stacked model and SVM ...

The incidences of fire and smoke in forests can result in significant damage and even casualties. Many recent detection methods lack generalization because they are mainly designed to suit specific ...

Building on random forests (RFs) and random intersection trees (RITs) and through extensive, biologically inspired simulations, we developed the iterative random forest algorithm (iRF). iRF trains a ...