Preparing for the midterm

The midterm exam will cover chapters 1 through 6 in the textbook. The exam will test your knowledge of key concepts in machine learning. I will pick several topics from the list below and ask you to write a short description of that concept to explain what it is for/and or what it does.

Here the list of questions you should be prepared to answer:

• What is regression?
• What is classification?
• What is cross validation?
• What is a decision function?
• What is a confusion matrix?
• How does the one-vs-all strategy differ from one-vs-one strategy?
• What is gradient descent?
• What is Logistic regression?
• What is polynomial regression?
• How does regularization help prevent overfitting?
• What is Ridge regression?
• What does a support vector machine seek to optimize?
• How do you construct a decision tree?