We can state the problem of learning decision trees as follows: We have a set of examples correctly categorised into categories (decisions). We also have a set of attributes describing the examples, ...

A decision tree classifier is a machine learning (ML) prediction system that generates rules ... The prediction accuracy of a minimal tree gives you a baseline comparison value. For example, suppose ...

there are other machine learning algorithms that are highly effective and also explainable. For example, decision tree-based learning algorithms, by nature, offer better explainability because the ...

A decision tree classifier is a machine learning (ML) prediction system that generates rules ... Figure 1: Splitting a Dataset Based on Gini Impurity The first example set of class labels is (0, 0, 2, ...

Decision trees are constructed by analyzing a set of training examples for which the class ... Boosting 10 is a machine-learning method used to combine multiple classifiers into a stronger ...

Machine learning is useful in parsing the immense amount of information that is consistently and readily available in the world to assist in decision making. Machine learning can be applied in a ...