Classification and Regression Using Supervised Learning
In this chapter, we are going to learn about classification and regression of data using supervised learning techniques. By the end of this chapter, you will have a better understanding of these topics:
- Differences between supervised and unsupervised learning
- Classification methods
- Data preprocessing methods
- Label encoding
- Logistic regression classifiers
- The Naïve Bayes classifier
- Confusion matrixes
- Support Vector Machines and SVM classifiers
- Linear and polynomial regression
- Single-variable and multivariable linear regressors
- Estimating housing prices using Support Vector Regressors
