Regressionstræer
Regressionstræer, also known as decision trees for regression, are a type of predictive modeling technique used in statistics and machine learning. Unlike classification trees, which predict categorical outcomes, regression trees predict continuous outcomes. They work by recursively partitioning the data into subsets based on the value of input features, creating a tree-like model of decisions.
The process begins with the root node, which represents the entire dataset. The algorithm then selects the
Regression trees have several advantages. They are easy to understand and interpret, as they can be visualized
However, regression trees also have some limitations. They can be prone to overfitting, especially if the tree
Regressionstræer are a fundamental tool in the field of machine learning and are used in a wide