Principal Geodesic Analysis
<p>PCA is a well-known technique for data analysis by representing the data in terms of its principal constituents. Two of the well-known applications of PCA are noise reduction and dimensionality reduction. Let’s review PCA with a simple example of noise reduction.</p>
<p>Real-world data are noisy. Noise can be introduced by the environment where we collect data or by the collection procedure itself. Let’s discuss the scenario in Figure 2.</p>
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