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Python Machine Learning (Wiley)

You're reading from  Python Machine Learning (Wiley)

Product type Book
Published in Apr 2019
Publisher Wiley
ISBN-13 9781119545637
Pages 320 pages
Edition 1st Edition
Languages
Author (1):
Wei-Meng Lee Wei-Meng Lee
Author Profile Icon Wei-Meng Lee
Wei-Meng Lee
Toc

Table of Contents (16) Chapters Close

1. Cover
2. Introduction
3. CHAPTER 1: Introduction to Machine Learning 4. CHAPTER 2: Extending Python Using NumPy 5. CHAPTER 3: Manipulating Tabular Data Using Pandas 6. CHAPTER 4: Data Visualization Using matplotlib 7. CHAPTER 5: Getting Started with Scikit‐learn for Machine Learning 8. CHAPTER 6: Supervised Learning—Linear Regression 9. CHAPTER 7: Supervised Learning—Classification Using Logistic Regression 10. CHAPTER 8: Supervised Learning—Classification Using Support Vector Machines 11. CHAPTER 9: Supervised Learning—Classification Using K‐Nearest Neighbors (KNN) 12. CHAPTER 10: Unsupervised Learning—Clustering Using K‐Means 13. CHAPTER 11: Using Azure Machine Learning Studio 14. CHAPTER 12: Deploying Machine Learning Models 15. Index
16. End User License Agreement

Types of Linear Regression

In the previous chapter, you learned how to get started with machine learning using simple linear regression, first using Python, and then followed by using the Scikit‐learn library. In this chapter, we will look into linear regression in more detail and discuss another variant of linear regression known as polynomial regression.

To recap, Figure 6.1 shows the Iris dataset used in Chapter 5, “Getting Started with Scikit‐learn for Machine Learning.” The first four columns are known as the features, or also commonly referred to as the independent variables. The last column is known as the label, or commonly called the dependent variable (or dependent variables if there is more than one label).

“Illustration presenting the Iris dataset in which the first 4 columns are called as the features, or independent variables and the last column is known as the label, or the dependent variable.”

Figure 6.1: Some terminologies for features and label

In simple linear regression, we talked about the linear relationship between...

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