In *Building Machine Learning and Deep Learning Models on Google Cloud Platform*, pages 231–241. Springer International Publishing Cham, 2019.

doi abstract bibtex

doi abstract bibtex

The fundamental idea behind the linear regression algorithm is that it assumes a linear relationship between the features of the dataset. As a result of the pre-defined structure that is imposed on the parameters of the model, it is also called a parametric learning algorithm. Linear regression is used to predict targets that contain real values. As we will see later in Chapter 20on logistic regression, the linear regression model is not adequate to deal with learning problems whose targets are categorical.

@incollection{borhani2022linear, abstract = {The fundamental idea behind the linear regression algorithm is that it assumes a linear relationship between the features of the dataset. As a result of the pre-defined structure that is imposed on the parameters of the model, it is also called a parametric learning algorithm. Linear regression is used to predict targets that contain real values. As we will see later in Chapter 20on logistic regression, the linear regression model is not adequate to deal with learning problems whose targets are categorical.}, author = {Bisong, Ekaba}, booktitle = {Building Machine Learning and Deep Learning Models on Google Cloud Platform}, doi = {10.1007/978-1-4842-4470-8_19}, pages = {231--241}, publisher = {Springer International Publishing Cham}, title = {{Linear Regression}}, year = {2019} }

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