So Lynch suggested something straight from her own research playbook: decision trees and random forests. Decision trees, Lynch explained, are machine learning algorithms that create chains of ...

Machine learning and ... from epoch to epoch. Specific algorithms have hyperparameters that control the shape of their search. For example, a Random Forest Classifier has hyperparameters for ...

To generate large and highly detailed forest maps, the researchers trained a type of machine learning algorithm called a deep neural network using images of the tree canopy and other sensor data ...

Random Forest, AdaBoost, and XGBoost. You’ll notice that there is some overlap between machine learning algorithms for regression and classification. A clustering problem is an unsupervised ...

New research shows machine-learning models predict suicide risk better than existing methods, emphasizing the critical role ...