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Data pre-processing

In this step, we apply some conversions to our data to make it consistent and concrete. There are lots of different conversions that you can consider while pre-processing your data:

  • Renaming (relabeling): This means converting categorical values to numbers, as categorical values are dangerous if used with some learning methods, and also numbers will impose an order between the values
  • Rescaling (normalization): Transforming/bounding continuous values to some range, typically [-1, 1] or [0, 1]
  • New features: Making up new features from the existing ones. For example, obesity-factor = weight/height
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