Which algorithm is typically faster to train on large datasets?

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Question: Which algorithm is typically faster to train on large datasets?

Options:

Correct Answer: Decision Trees

Solution:

Decision Trees are generally faster to train than Random Forests, as Random Forests require training multiple trees.

Which algorithm is typically faster to train on large datasets?

Which algorithm is typically faster to train on large datasets?

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.

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