Chapter 3. Predictive Modeling

In this chapter, we will cover the following recipes:

  • Building a linear classifier using Support Vector Machines (SVMs)
  • Building a nonlinear classifier using SVMs
  • Tackling class imbalance
  • Extracting confidence measurements
  • Finding optimal hyperparameters
  • Building an event predictor
  • Estimating traffic
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