Classification vs Regression, Supervised vs Unsupervised Machine Learning

profileabhilash tati

 

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Chapter 2 An Introduction to Statistical Learning http://www-bcf.usc.edu/~gareth/ISL/index.html

2 Statistical Learning 15

2.1 What Is Statistical Learning? . . . . . . . . . . . . . . . . . 15

2.1.1 Why Estimate f? . . . . . . . . . . . . . . . . . . . . 17

2.1.2How Do We Estimate f? . . . . . . . . . . . . . . . 21

2.1.3 The Trade-Off Between Prediction Accuracy and Model Interpretability . . . . . . . . . . . . . . 24

2.1.4 Supervised Versus Unsupervised Learning . . . . . . 26

2.1.5 Regression Versus Classification Problems . . . . . . 28

2.2 Assessing Model Accuracy . . . . . . . . . . . . . . . . . . . 29

2.2.1 Measuring the Quality of Fit . . . . . . . . . . . . . 29

2.2.2 The Bias-Variance Trade-Off . . . . . . . . . . . . . 33

2.2.3 The Classification Setting . . . . . . . . . . . . . . . 37

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