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Dimensionality Reduction

  • Q. What is Dimensionality Reduction?
  • Q. What is Principal Component Analysis (PCA), and how does it differ from clustering?
  • Q. What is Kernel PCA?
  • Q. What is Independent Component Analysis (ICA), and how is it distinguished from PCA?
  • Q. What is Factor Analysis, and how does it differ from PCA?
  • Q. How does T-distributed Stochastic Neighbor Embedding (T-SNE) work at a high level?
  • Q. How does T-SNE compare to PCA?
  • Q. What is Random Projection? Discuss its advantages and disadvantages?
  • Q. When to use PCA vs Random Projection?
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Other Questions in Dimensionality Reduction
  • Top 20 Interview Questions on Ensemble Learning with detailed Answers (All free)
  • What is a Decision Tree? Explain the concept and working of a Decision tree model
  • What is Bagging? How do you perform bagging and what are its advantages?
  • Explain the concept and working of the Random Forest model
  • What are the advantages and disadvantages of Decision Tree model? 
  • What are the advantages and disadvantages of Random Forest?
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