Which of the following techniques is primarily used for dimensionality reduction in datasets with many features?

  • Apriori Algorithm
  • Breadth-First Search (BFS)
  • Linear Regression
  • Principal Component Analysis (PCA)
Principal Component Analysis (PCA) is a dimensionality reduction technique used to reduce the number of features while preserving data variance.
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