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Missing Value Handling - exercise

Data manipulation Preprocessing Missing value MCAR MAR
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Introduction to Machine Learning Algorithms course - Session 4 Exercise 2 Handle missing values in the data by - Setting them to a fixed value (zero) - Generating a dummy column based on missing values in another column - Replacing them with the column mean or the most frequent value in the column - Looking for different missing value patterns in the data - Filtering out columns that have many missing values

External resources

  • Slides (Introduction to ML Algorithms course)
  • Ames Housing Dataset on kaggle
  • Description of the Ames Iowa Housing Data

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Created with KNIME Analytics Platform version 4.5.0
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