Gradient Boosting Machine (GBM) is a powerful machine learning algorithm that is used for both classification and regression tasks. It is a type of ensemble learning method, which means it combines multiple weak models to create a strong model. GBM is a popular algorithm for data science and machine learning projects because it is …
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 …