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04_Dimensionality_Reduction_solution

Dimensionality reductionData manipulationPreprocessingPCAFeature importance
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Feb 5, 2025 6:46 PM
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Dimensionality Reduction - solution

Introduction to Machine Learning Algorithms course - Session 4
Solution to exercise 4
Apply the following dimensionality reduction techniques to the data:
- Filter out columns with a low variance
- Filter out one of two columns with a high linear correlation
- Replace numeric columns with principal components
- Filter out columns which are not important in predicting the target column

External resources

  • Slides (Introduction to ML Algorithms course)
  • 3 New Techniques for Data-Dimensionality Reduction in Machine Learning
  • Seven Techniques for Data Dimensionality Reduction
  • Description of the Ames Iowa Housing Data
  • Ames Housing Dataset on kaggle
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