Department of Orthopedics, Shanxi Bethune Hospital, Tongji Shanxi Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Taiyuan, China Background and aim: ...

Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...

Comparing Random Survival Forests and Cox Regression for Nonresponders to Neoadjuvant Chemotherapy Among Patients With Breast Cancer: Multicenter Retrospective Cohort Study ...

1 Department of Neurology, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China 2 Support Centre, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China Background and aim: ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...

A machine learning random forest regression system predicts a single numeric value. A random forest is an ensemble (collection) of simple decision tree regressors that have been trained on different ...

Abstract: In this work, a random forest regression was used to predict the temperature of an interferometric optical sensor over a wide measurement range, overcoming several times the $2\pi $ ...

We must change course. The climate crisis is deepening, and the SDGs are veering off course. Forests stand as the bedrock of our journey towards a net-zero, climate-resilient, and equitable future for ...