Predicting Price. of used cars. The DataToyotaCorolla.csv file contains data on sales of used Toyota Corolla cars. It ha

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Predicting Price. of used cars. The DataToyotaCorolla.csv filecontains data on sales of used Toyota Corolla cars. It has 1436records containing details on 38 attributes, including Price, Age,Kilometers, HP, and other specifications. The goal is to predictthe price of a used Toyota Corolla based on its specifications.
1. Create dummy variables for the categorical predictors andrename the file into TrainingDataToyotaCorolla.csv. Provide theused references in your report.
2. Using Python, run a multiple linear regression with theoutput variable Price and input variables Age 08 04, KM, FueLType,HP, Automatic, Doors, Quarterly Tax, Mfr Guarantee, GuaranteePeriod, Airco, Automatic_Aireo, CD Player, Powered_Windows,Sport-Model, and Tow_Bar. What appear to be the four most importantcar specifications for predicting the car's price? Specify thePartial Search Algorithms used to determine that.
3. Use Python to predict the prices of the two cars in theTestingDataToyotaCorolla.csv file using the four car specificationsselected requirement number 2.
4. Use Python to build K NN classification models usingTrainingDataToyotaCorolla.csv file with k = 5 and K=10. Determinewhich K gives a better prediction accuracy and use it to predictthe prices of the two cars in the TestingDataToyotaCorolla.csvfile.
5. Compare the prediction performance of multiple linearregression achieved in requirement 3 and the KNN classifierachieved in requirement 4.
Sample of the data
Please send me the code for all requirements mentionedabove.