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COMP 1942 PCA TA: Harry Chan Email: khchanak@ust.hk COMP1942.

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Presentation on theme: "COMP 1942 PCA TA: Harry Chan Email: khchanak@ust.hk COMP1942."— Presentation transcript:

1 COMP 1942 PCA TA: Harry Chan COMP1942

2 Outline PCA Review PCA in XLMiner COMP1942

3 Review: PCA Dimension reduction Many dimensions
Correlation among dimensions 3-dimensional: (1, 2, 3), (2, 4, 7), (5, 10, 8), … 2-dimensional: (1, 3), (2, 7), (5, 8), … COMP1942

4 Using PCA in XLMiner Two ways to access PCA
“Add-ins” Tag  XLMiner  Data Reduction and Exploration  Principal Components Analysis “XLMiner Platform” Tag  Transform  Principal Components Analysis COMP 1942

5 Steps Step 1: Specify the data range and variables.
Step 2: Specify the principal components and method. Step 3: Specify the output options. COMP1942

6 Step 1 Data Source Variables COMP1942

7 Step 2 Fixed # of components Use Covariance Matrix COMP1942

8 Show principal components score
Step 3 Show principal components score COMP1942

9 Example Dataset: Utilities.xls Parameters
22 public utilities in the US 8 dimensions (x1-x8) Parameters Fixed # components: 6 Use Covariance Matrix Show principal components score COMP1942

10 Results COMP1942

11 Results Transformed data COMP1942

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