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Standardization of Featureless Variables for Machine Learning Models Using Natural Language Processing

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10861)

Abstract

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.

Keywords

Machine learning Natural Language Processing Mixed type variables 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Adobe Inc.San JoseUSA

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