Reconstructing Improper Values with Local Centered Moving Trimmed Mean¶
This step replaces any improper values in the data vector with the Trimmed Mean of the neighbourhood values and is resistant to outliers.
- Input data including improper values
- Definition of improper values (‘nan’, ‘inf’, or ‘null’, etc.)
- Percentage of high and low extremes to be trimmed
- Local window size
- Output data excluding improper values
- J. Han, M. Kamber and J. Pei, Data Mining - Concepts and Techniques, 3rd ed., Amsterdam: Morgan Kaufmann Publishers, 2012.