Principle Component Analysis

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Across
  1. 2. MATRIX Matrix that PCA decomposes to find directions of maximum variance
  2. 4. PLOT that shows how much variance each principal component explains (two words)
  3. 5. The first principal component always captures the maximum amount of this
Down
  1. 1. PCA reduces this property of data while keeping most information
  2. 3. New transformed variables created by PCA