What is the primary goal of the Principal Component Analysis (PCA) technique in machine learning?
- Clustering Data
- Finding Anomalies
- Increasing Dimensionality
- Reducing Dimensionality
PCA's primary goal is to reduce dimensionality by identifying and retaining the most significant features, making data analysis and modeling more efficient.
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