City College, Fall 2019
Intro to Data Science
Week 6: Regression vs. Classification
October 16, 2019Today's Agenda
- Regression vs. Classification
- Logistic Regression
- Measuring Performance for Classification Models
Week 5 Recap
- Linear Regression
- Assumptions for Linear Models
- Measuring Performance for Linear Models
Data Science Models
Generalized Linear Models
A flexible generalization of ordinary linear regression that allows for response variables that have error distribution models other than a normal distribution.
Generalized Linear Models
Regression vs. Classification
Is this a good forecast?
Regression analysis estimates the conditional expectation of the dependent variable given the independent variables.
Classification is the problem of identifying to which of a set of categories a new observation belongs.
Regression vs. Classification
Logistic Regression
Solved by gradient descent. (optimization)
Logistic Regression
Regression vs. Classification
Logistic Regression Output
Logisitic regression and many other classification models output a continuous value between 0 and 1.
Measuring Classification Performance
- Confusion Matrix
- Precision
- Recall
- Accuracy
Confusion Matrix
Precision
zombie apocalypse use case: you're hunting zombies, and you need to kill as many zombies as possible without killing any humans
Recall
zombie apocalypse use case: you discover a cure for zombies, but can only apply it k infected people
Accuracy
zombie apocalypse use case: zombies have infected roughly half the population, and you're throwing them a party. you are putting together an invite list and want to make sure you invite an equal amount of zombies and humans.
Assignment 6: Due Thursday, October 24 by 11:59pm
DataCamp's Machine Learning with Tree-Based Models in Python
- The course should appear collectively as assignment within your existing DataCamp account.
- Course claims to take 5 hours, but I found it shorter than some of the past courses. Nonetheless, use your time wisely.