Numerical Coding of Nominal Data
This addresses the problem of handling nominal data in classification tasks for data scientists, though it appears incremental as it builds on existing coding methods.
The paper tackles the problem of coding nominal data by assigning complex number ranks, which preserves all attribute information and introduces new properties. The result is that classification using the coded nominal data, either alone or combined with numerical data, is more effective than using only numerical data.
In this paper, a novel approach for coding nominal data is proposed. For the given nominal data, a rank in a form of complex number is assigned. The proposed method does not lose any information about the attribute and brings other properties previously unknown. The approach based on these knew properties can been used for classification. The analyzed example shows that classification with the use of coded nominal data or both numerical as well as coded nominal data is more effective than the classification, which uses only numerical data.