QA 15. Machine Learning and Prediction

Learning Objectives

1) Explain the role of linear regression and logistic regression in prediction.

2) Understand how to encode categorical variables.

3) Discuss why regularization is useful, and distinguish between the ridge regression and LASSO approaches.

4) Show how a decision tree is constructed and interpreted.

5) Describe how ensembles of learners are built.

6) Outline the intuition behind the K nearest neighbors and support vector machine methods for classification.

7) Understand how neural networks are constructed and how their weights are determined.

8) Evaluate the predictive performance of logistic regression models and neural network models using a confusion matrix.