Great work! You've learned about two fundamental supervised learning algorithms. As a quick recap, linear regression predicts a continuous numerical value (like a price), while logistic regression predicts the probability of a categorical outcome (like 'yes' or 'no').
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Type
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Practice Question
For each of the following problems, decide if it's a better fit for Linear Regression or Logistic Regression.
Labels
- Left Label: Linear Regression
- Right Label: Logistic Regression
Left Label Items
- Predicting the temperature tomorrow.
- Estimating the number of monthly sales for a new product.
- Forecasting a company's stock price next week.
Right Label Items
- Determining if a credit card transaction is fraudulent.
- Predicting whether a customer will unsubscribe from a service.
- Classifying a tumor as benign or malignant.
Type
Fill In The Blanks
Markdown With Blanks
A linear regression model for predicting a car's fuel efficiency (in MPG) based on its weight is given by the equation: MPG = -0.01 * weight + 50
.
Use this model to fill in the blanks and predict the MPG for a car that weighs 2,500 lbs.
Suggested Answers
- -25
- 25
- -50
- 75
