- Start: Monday, October 06
- End: Saturday, October 11
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