Chapter 2. Constructing a Classifier
In this chapter, we will cover the following recipes:
- Building a simple classifier
- Building a logistic regression classifier
- Building a Naïve Bayes classifier
- Splitting the dataset for training and testing
- Evaluating the accuracy using cross-validation
- Visualizing the confusion matrix
- Extracting the performance report
- Evaluating cars based on their characteristics
- Extracting validation curves
- Extracting learning curves
- Estimating the income bracket
Introduction
In the field of machine learning, classification refers to the process of using the characteristics of data to separate it into a certain number of classes. This is different from regression that we discussed in the previous chapter where the output is a real number. ...
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