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Random Forest Variable Importance: Calculation, Accuracy, & Examples
Learn how variable importance is calculated in random forests using both accuracy-based and Gini-based measures.
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How Random Forests Fit to Data
A random forest is a collection of decision trees, which is used to learn patterns in data and make predictions based on those patterns.
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What is a Random Forest?
A random forest is an ensemble of decision trees. Like other machine-learning techniques, random forests use training data to learn to make predictions.
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