Use scaling algorithms to reduce the data values to a specific range using a mathematical transformation. For example, the DCPY.MAXABSSCALER algorithm reduces the absolute data values to the [0, 1] range by dividing each value by the largest absolute value in the column. Data scaling is a recommended pre-processing step when working with many machine learning algorithms.те
The following algorithms are available:
- DCPY.MINMAXSCALER(feature_range_min, feature_range_max, column)
- DCPY.ROBUSTSCALER(with_centering, with_scaling, quantile_range_min, quantile_range_max, column)
- DCPY.STANDARDSCALER(with_mean, with_std, column)
The SCRIPT function can be used to run your custom algorithm based on the available AI connection. For details, see Add script calculations.