ML Studio also comes with advanced data processing options. The following are some of the common options that are discussed in brief.
Outliers are data points that are distinctly separate from the rest of the data. Outliers, if present in your dataset, may cause problems by distorting your predictive model that may result in an unreliable prediction of the data. In many cases, it is a good idea to clip or remove the outliers.
ML Studio comes with the Clip Values module, which detects outliers and lets you clip or replace values with a threshold, mean, median, or missing value. By default, it is applied to all the numeric columns, but you can select one or more columns. You can find it by navigating to Data Transformation | Scale and then Reduce in the module palette.
