Many machine learning algorithms perform better when numerical input variables are scaled to a standard range.
- You will discover how to use robust scaler transforms to standardize numerical input variables for classification and regression.
After completing this tutorial, you will know:
- Many machine learning algorithms prefer or perform better when numerical input variables are scaled.
- Robust scaling techniques that use percentiles can be used to scale numerical input variables that contain outliers.
- How to use the RobustScaler to scale numerical input variables using the median and interquartile range.
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