Abstract
As we talked about Machine Learning in the previous chapter, it’s a very vast field and there are multiple algorithms that fall under various categories, but Linear Regression is one of the most fundamental machine learning algorithms. This chapter focuses on building a Linear Regression model with PySpark and dives deep into the workings of an LR model. It will cover various assumptions to be considered before using LR along with different evaluation metrics. But before even jumping into trying to understand Linear Regression, we must understand the types of variables.
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© 2019 Pramod Singh
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Singh, P. (2019). Linear Regression. In: Machine Learning with PySpark . Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4131-8_4
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DOI: https://doi.org/10.1007/978-1-4842-4131-8_4
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4130-1
Online ISBN: 978-1-4842-4131-8
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