Machine learning depends on a number of algorithms for turning a data set into a model ... methods (combinations of models), such as Random Forest, other Bagging methods, and boosting methods ...

Machine learning algorithms are the engines of machine learning, meaning it is the algorithms that turn a data set into a model ... For example, a Random Forest Classifier has hyperparameters ...

Budoen, A.T., Zhang, M.W. and Edwards Jr., L.Z. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, ...

As part of the first project, we created a data set of ecological ... decision trees and random forests. Decision trees, Lynch explained, are machine learning algorithms that create chains of ...

and selected the Random Forest algorithm to identify threats in encrypted communication traffic. This mature Machine Learning (ML) algorithm produces an identification accuracy higher than 99%.

A study reveals machine learning algorithms can predict compressive strength in concrete with waste glass powder, enhancing ...

In order to turn a low-resolution image into a high-resolution one, the software has to fill in the blanks using machine learning ... far deeper than any dataset or algorithm.