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How do Random Forests improve prediction accuracy?
How do Random Forests improve prediction accuracy?
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Practice Questions
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Q1
How do Random Forests improve prediction accuracy?
By using a single Decision Tree
By averaging predictions from multiple trees
By reducing the number of features
By increasing the depth of trees
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Random Forests improve accuracy by averaging the predictions from multiple Decision Trees.
Questions & Step-by-step Solutions
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Q
Q: How do Random Forests improve prediction accuracy?
Solution:
Random Forests improve accuracy by averaging the predictions from multiple Decision Trees.
Steps: 6
Show Steps
Step 1: Understand that a Decision Tree is a model that makes predictions based on data features.
Step 2: Realize that a single Decision Tree can make mistakes and may not always be accurate.
Step 3: Learn that a Random Forest is made up of many Decision Trees working together.
Step 4: Know that each tree in the Random Forest makes its own prediction based on the data.
Step 5: Understand that the Random Forest takes the average of all the predictions from the trees.
Step 6: Recognize that averaging helps to reduce errors and improve overall accuracy.
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