Python Machine Learning Cookbook
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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