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Which algorithm is typically faster to train on large datasets?
Practice Questions
Q1
Which algorithm is typically faster to train on large datasets?
Decision Trees
Random Forests
Both are equally fast
Neither, both are slow
Questions & Step-by-Step Solutions
Which algorithm is typically faster to train on large datasets?
Steps
Concepts
Step 1: Understand that Decision Trees are a type of algorithm used for making predictions based on data.
Step 2: Learn that Random Forests are an extension of Decision Trees that create many trees to improve accuracy.
Step 3: Recognize that training a single Decision Tree is quicker because it only involves one tree.
Step 4: Realize that Random Forests train multiple Decision Trees, which takes more time.
Step 5: Conclude that for large datasets, Decision Trees are typically faster to train than Random Forests.
No concepts available.
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