AI and machine learning are mathematical modeling methods for learning from data and producing intelligent models based on this learning. The data these models need to deal with, is normally a mixed of data type where both numerical (continuous) variables and categorical (non-numerical) data types. Most models in AI and machine learning accept only numerical data as their input and thus, standardization of mixed data into numerical data is a critical step when applying machine learning models. Having data in the standard shape and format that models require often a time consuming, nevertheless very significant step of the process.
CITATION STYLE
Modarresi, K., & Munir, A. (2018). Standardization of Featureless Variables for Machine Learning Models Using Natural Language Processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10861 LNCS, pp. 234–246). Springer Verlag. https://doi.org/10.1007/978-3-319-93701-4_18
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