Are you passionate about cutting-edge research that bridges the digital and physical worlds? The School of Internet of Things at XJTLU is seeking talented researchers to join our innovative project on ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

Machine Learning project to predict water potability using supervised learning algorithms with data preprocessing, model comparison, and deployment using Gradio. Gradio. data preprocessing, model ...

Abstract: Above-ground forest biomass is an important evaluation indicator of forest productivity and carbon balance. The random forest method is currently a relatively mature machine learning method ...

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...

Abstract: This work proposes a hybrid classification model using CNN–Random Forest for the six banana leaf diseases from the 12,825 image dataset. The model is trained and tested against the classes ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Tumor neoantigens possess high specificity and immunogenicity, making them crucial targets for personalized cancer immunotherapies such as mRNA vaccines and T-cell therapies. However, experimental ...

The machine learning model was significantly better than parametric logistic regression and LASSO models for predicting inpatient mortality. HealthDay News — For inpatients with cirrhosis, a machine ...