For example, households can be classified into those that ... Instead of creating a single decision tree, the Random Forest algorithm can create many individual trees from randomly selected subsets of ...

However, it's not a bad idea to normalize the predictors just in case you want to send the data to other regression algorithms that require normalization (for example, k-nearest neighbor regression).

Specific algorithms have hyperparameters that control the shape of their search. For example, a Random Forest Classifier has hyperparameters for minimum samples per leaf, max depth, minimum ...

automatic sample selection using Machine Learning (Random Forest) techniques for algorithm training using plant height as a discriminating variable; (iii) automatic classification and generation of ...