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This chapter focuses on principal component analysis (PCA). We have covered how to implement PCA with NumPy and how to use the PCA class from scikit-learn in Chap. 4. This chapter further shows how SymPy can help us understand the mathematical theory behind PCA. At the end of this chapter, we shall apply PCA on a randomly sampled dataset to demonstrate the importance of normalising data before undertaking PCA.

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Algorithms 1—Principal Component Analysis

  • 章节

  • 发表日期：

    2026年

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  • Yi Sun,
  • Rod Adams

摘要

This chapter focuses on principal component analysis (PCA). We have covered how to implement PCA with NumPy and how to use the PCA class from scikit-learn in Chap. 4. This chapter further shows how SymPy can help us understand the mathematical theory behind PCA. At the end of this chapter, we shall apply PCA on a randomly sampled dataset to demonstrate the importance of normalising data before undertaking PCA.