METHOD FOR CONVERTING NOMINAL TO ORDINAL OR CONTINUOUS VARIABLES USING TIME-SERIES DISTANCES

A method and system for converting non-ordered categorical data stored within a column in a data set into an ordered or continuous data stored in a new column within the data set. Each distinct categorical value in the nominal data column is represented by a corresponding distinct numerical value in the new column. The new representative numerical values are derived by constructing separate time series for each distinct value in the nominal data column and by calculating the similarities between the shapes of the time series. The proximity of the time series is captured in a numeric distance score. Each distinct distance score corresponds to a distinct value in the nominal data column and is a valid representation of that value in machine learning, deep learning, and statistical analysis.