01_​Missing_​Value_​Handling

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Missing Value Handling - exercise

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

URL: Description of the Ames Iowa Housing Data https://rdrr.io/cran/AmesHousing/man/ames_raw.html
URL: Ames Housing Dataset on kaggle https://www.kaggle.com/prevek18/ames-housing-dataset
URL: Slides (Introduction to ML Algorithms course) https://www.knime.com/form/material-download-registration

Nodes

• Rule Engine3 ×
• CSV Reader1 ×
• Column Auto Type Cast1 ×
• Column Filter1 ×
• Missing Value1 ×
• Show all 7 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Javasnippet

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