Link to mybinder:

Assignment-8

https://think.cs.vt.edu/corgis/csv/cars/cars.html

Exercises

Download the data

• Programatically download the data from the above link.
• Import the data into a Pandas dataframe.
• Show the head of the Pandas dataframe.

Linear regression

• Perform linear regression on the downloaded dataset, where y=Highway mpg and x=Horsepower.
• What is the coefficient (slope) of your model? What does this number mean?
• According to your model, what is y when x=2000.
• Show the regression line on a scatterplot with the other datapoints.

Classification

• Using sklearn create a classifier that can predict the make of a car, based on provided features. The following features should be included:
  • City mpg
  • Highway mpg
  • Height
  • Width
  • Length
  • Horsepower
  • Year
• Show the decisiontree of your model.
• Use your model to predict the make of a car.

Review questions

1. Did the student programatically download and import the data?
2. Did the student correctly display the regression line in a graph`?
3. Did the student find the coefficient of the line, and reflect on its meaning?
4. Did the student correctly provide their classification model with imported data?