Abstract
Regression models allow you to include as many independent variables as you want. In traditional regression analysis, there are good reasons to limit the number of variables. The spirit of exploratory data mining, however, encourages examining a large number of independent variables. Here we are presenting very small models for demonstration purposes. In data mining applications, the assumption is that you have very many observations , so that there is no technical limit on the number of independent variables.
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Olson, D.L., Wu, D. (2017). Multiple Regression. In: Predictive Data Mining Models. Computational Risk Management. Springer, Singapore. https://doi.org/10.1007/978-981-10-2543-3_4
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DOI: https://doi.org/10.1007/978-981-10-2543-3_4
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