Abstract
It is essential to extract useful knowledge from data for decision making. However, the entire data is not always processing ready. It may contain noise, missing values, redundant attributes, etc., so data preprocessing is one of the most important steps to make data ready for final processing. Feature selection is an important task used for data preprocessing. It helps reduce the noise, redundant, and misleading features. Based on its importance, in this chapter, we will focus on feature selection and different concepts associated with it.
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© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Qamar, U., Raza, M.S. (2020). Data Preprocessing. In: Data Science Concepts and Techniques with Applications. Springer, Singapore. https://doi.org/10.1007/978-981-15-6133-7_4
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DOI: https://doi.org/10.1007/978-981-15-6133-7_4
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