@incollection{Borhani2022,
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.},
address = {Cham},
author = {Borhani, Reza and Borhani, Soheila and Katsaggelos, Aggelos K.},
booktitle = {Fundamentals of Machine Learning and Deep Learning in Medicine},
doi = {10.1007/978-3-031-19502-0_4},
pages = {69--87},
publisher = {Springer International Publishing},
title = {{Linear Regression}},
url = {https://link.springer.com/10.1007/978-3-031-19502-0_4},
year = {2022}
}

{"_id":"W6TX5X5MWnABayJ5D","bibbaseid":"borhani-borhani-katsaggelos-linearregression-2022","author_short":["Borhani, R.","Borhani, S.","Katsaggelos, A. K."],"bibdata":{"bibtype":"incollection","type":"incollection","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.","address":"Cham","author":[{"propositions":[],"lastnames":["Borhani"],"firstnames":["Reza"],"suffixes":[]},{"propositions":[],"lastnames":["Borhani"],"firstnames":["Soheila"],"suffixes":[]},{"propositions":[],"lastnames":["Katsaggelos"],"firstnames":["Aggelos","K."],"suffixes":[]}],"booktitle":"Fundamentals of Machine Learning and Deep Learning in Medicine","doi":"10.1007/978-3-031-19502-0_4","pages":"69–87","publisher":"Springer International Publishing","title":"Linear Regression","url":"https://link.springer.com/10.1007/978-3-031-19502-0_4","year":"2022","bibtex":"@incollection{Borhani2022,\nabstract = {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.},\naddress = {Cham},\nauthor = {Borhani, Reza and Borhani, Soheila and Katsaggelos, Aggelos K.},\nbooktitle = {Fundamentals of Machine Learning and Deep Learning in Medicine},\ndoi = {10.1007/978-3-031-19502-0_4},\npages = {69--87},\npublisher = {Springer International Publishing},\ntitle = {{Linear Regression}},\nurl = {https://link.springer.com/10.1007/978-3-031-19502-0_4},\nyear = {2022}\n}\n","author_short":["Borhani, R.","Borhani, S.","Katsaggelos, A. K."],"key":"Borhani2022","id":"Borhani2022","bibbaseid":"borhani-borhani-katsaggelos-linearregression-2022","role":"author","urls":{"Paper":"https://link.springer.com/10.1007/978-3-031-19502-0_4"},"metadata":{"authorlinks":{}}},"bibtype":"incollection","biburl":"https://sites.northwestern.edu/ivpl/files/2023/06/IVPL_Updated_publications-1.bib","dataSources":["zFPgsTDAW8aDnb5iN","E6Bth2QB5BYjBMZE7","nbnEjsN7MJhurAK9x","PNQZj6FjzoxxJk4Yi","7FpDWDGJ4KgpDiGfB","bod9ms4MQJHuJgPpp","QR9t5P2cLdJuzhfzK","D8k2SxfC5dKNRFgro","7Dwzbxq93HWrJEhT6","qhF8zxmGcJfvtdeAg","fvDEHD49E2ZRwE3fb","H7crv8NWhZup4d4by","DHqokWsryttGh7pJE","vRJd4wNg9HpoZSMHD","sYxQ6pxFgA59JRhxi","w2WahSbYrbcCKBDsC","XasdXLL99y5rygCmq","3gkSihZQRfAD2KBo3","t5XMbyZbtPBo4wBGS","bEpHM2CtrwW2qE8FP","teJzFLHexaz5AQW5z"],"keywords":[],"search_terms":["linear","regression","borhani","borhani","katsaggelos"],"title":"Linear Regression","year":2022}