Decision Tree
A Decision Tree is a non-parametric supervised learning method used for both classification and regression. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features.
Frequently Asked Questions
What is a node in a decision tree?▼
A split condition based on a feature value. The leaves represent final target outcomes or classifications.
What is the main drawback of decision trees?▼
They are highly prone to overfitting the training data, which is typically resolved by pruning the tree or using random forests.
Quick Facts
- CategoryFoundational AI
- Key ApplicationCustomer churn prediction, medical diagnosis tree diagrams, and baseline classification.
Coverage Trend12 Weeks
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