For high-dimensional data, _______ is a technique used to reduce the number of input variables.

  • Decision Trees
  • Normalization
  • Principal Component Analysis (PCA)
  • Regression Analysis
Principal Component Analysis (PCA) is a technique commonly employed to reduce the dimensionality of high-dimensional data by transforming it into a new set of uncorrelated variables (principal components). Regression, Decision Trees, and Normalization serve different purposes in data analysis.
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