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This is the second part of “Supervised Learning: Regressions”. There is a good chance that most readers and students have learned this part already. It might be a good idea for those readers to go through this chapter quickly or skip it to save time. We start with the simple ones: linear regressionsLinear regression, such as one-factor linear regressionsLinear regression, multi-variable regressions, collinearityCollinearity, dummy variablesDummy variable for categorical variablesCategorical variables, and linear models for non-linear variablesNon-linear variables. In addition, we will use several examples for Logistic RegressionsLogistic regression. In this chapter, the following topics will be covered.

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Supervised Learning (II): Regressions

  • 章节

  • 发表日期：

    2025年

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  • Yuxing Yan

摘要

This is the second part of “Supervised Learning: Regressions”. There is a good chance that most readers and students have learned this part already. It might be a good idea for those readers to go through this chapter quickly or skip it to save time. We start with the simple ones: linear regressionsLinear regression, such as one-factor linear regressionsLinear regression, multi-variable regressions, collinearityCollinearity, dummy variablesDummy variable for categorical variablesCategorical variables, and linear models for non-linear variablesNon-linear variables. In addition, we will use several examples for Logistic RegressionsLogistic regression. In this chapter, the following topics will be covered.