Enhancing Hairfall Prediction: A Comparative Analysis of Individual Algorithms and an Ensemble Method
TLDR Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
This research paper demonstrates that an ensemble machine learning approach significantly enhances the prediction of hair fall compared to individual algorithms. By combining the strengths of various algorithms, the ensemble models achieve higher accuracy, precision, and recall, effectively identifying both hair fall and non-hair fall instances. This comprehensive and robust prediction framework offers valuable insights for early detection and intervention, aiding in hair loss prevention and maintenance of hair health.
