Text and data formatting for machine learning

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Abstract

Machine learning is a prominent tool for getting data from large amounts of information. Whereas a good amount of machine learning analysis has targeted on increasing the accuracy and potency of coaching and reasoning algorithms, there is less attention within the equally vital issues of observing the standard of information fed into the machine learning model. The standard of huge information is far away from good. Recent studies have shown that poor quality will bring serious errors to the result of big data analysis and this could have an effect on in making additional precise results from the information. Advantages of data preprocessing within the context of ML are advanced detection of errors, model-quality improves by the usage of better data, savings in engineering hours to debug issues.

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Chelliah, B. J., Jain, A., Singh, U., & Mehta, G. (2019). Text and data formatting for machine learning. International Journal of Innovative Technology and Exploring Engineering, 9(1), 2756–2760. https://doi.org/10.35940/ijitee.A5216.119119

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