Summary

This week, we will discuss binary classification in depth, in particular, metrics for evaluating binary classification models. We will also take a look at a linear model for classification, logistic regression, a parametric model. We will begin to compare and contrast parametric and nonparametric methods.

Learning Objectives

After completing this week, you are expected to be able to:

  • Understand the definitions of false positives, false negatives, and related metrics.
  • Calculate metrics specific to binary classification.
  • Evaluate models for binary classification.
  • Differentiate between parametric and nonparametric regression.
  • Estimate conditional probabilities with logistic regression.
  • Use sklearn to fit logistic regression models and make predictions for unseen data.
  • Preprocess data to add polynomial and interaction terms for use in linear models.

Topics

  • Binary Classification
  • Binary Classification Metrics
  • Model Evaluation
  • Logistic Regression
  • Parametric versus Nonparametric Models

Activities