Machine Learning Fundamental [ Question - 18]
[Machine Learning
Which statement is correct about Random forest classifiers?
The trees within forest randomly sample from the dataset with replacement
The trees within forest must be strongly correlated
The trees within forest mostly use the same features
The trees within forests are individually insensitive to data changes



Answer :

Final answer:

Random Forest classifiers randomly sample data, are individually insensitive to data changes, and do not need to be strongly correlated.


Explanation:

The correct statement about Random Forest classifiers is:

  • The trees within the forest randomly sample from the dataset with replacement, which contributes to the diversity of the trees.
  • These trees within the forest are individually insensitive to data changes, as each tree is trained independently.
  • Contrary to the statement provided, the trees within the forest do not have to be strongly correlated; in fact, their independence is crucial for the effectiveness of Random Forest.

Learn more about Random Forest classifiers here:

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