Introduction to Introduction to Sensory Data Analysis - Camo
Introduction to Introduction to Sensory Data Analysis - Camo
Introduction to Introduction to Sensory Data Analysis - Camo
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4. Principal Component <strong>Analysis</strong>: PCA / a) Theory<br />
Principal Component <strong>Analysis</strong> (PCA)<br />
•Explora<strong>to</strong>ry data analysis<br />
•Extract information<br />
• Noise removal<br />
• Dimensionality reduction<br />
<strong>Data</strong> structure in PCA:<br />
• Each row represents an observation<br />
• Each column represents a variable<br />
Variable 1 Variable 2 Variable 3<br />
Object 1<br />
Object 2<br />
Object 3<br />
Object 4<br />
X Model Error<br />
<strong>Data</strong> Structure Noise
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