Random Forest is a type of ensemble learning method, which is used to build a model by combining multiple decision trees. The main idea behind using Random Forest is that multiple decision trees will provide a more accurate and stable prediction than a single decision tree. The Boston Housing Price dataset from UCI …
Decision trees are a popular machine learning algorithm that can be used for both classification and regression tasks. They work by creating a tree-like structure where each internal node represents a feature and each leaf node represents a prediction. The algorithm starts at the root of the tree and makes a decision …