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