Training and evaluation turn supervised learning algorithms into models by optimizing their parameters to find ... For example, a Random Forest Classifier has hyperparameters for minimum samples ...

You can also use ensemble methods (combinations of models), such as Random Forest ... Training and evaluation turn supervised learning algorithms into models by optimizing their parameter weights ...

In the model acquisition phase, extraneous features are used as input components for machine learning, and a random forest algorithm ... and efficiency parameters. K-Nearest Neighbor (K-NN) is a ...