Chapter 7. Estimating the Likelihood of Events

Logistic regression is a type of regression analysis that helps in estimating the likelihood of an event to occur based on some given parameters. It is used as a classification technique with a binary outcome. The probabilities describing the possible outcomes of a single trial are modeled, as a function of the explanatory (predictor) variables, using a logistic function.

You have been already introduced to Logisitc regression in Chapter 5, Uncovering Machine Learning. In this chapter, you'll learn to:

  • Build a logistic regression model with statsmodels
  • Build a logistic regression model with SciKit
  • Evaluate and test the model

Logistic regression

We'll use the Titanic dataset, which was utilized in Chapter ...

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