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For the variables with the 2/1 scores, replace all the 2 with a Yes and 1 with a No

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We will use the following dataset (“mini survey lung cancer.csv”) to predict Lunch Cancer. It is a comma separated file and the variables present in the file are : GENDER, AGE, SMOKING, ANXIETY, CHRONIC DISEASE, ALCOHOL CONSUMING, SHORTNESS OF BREATH, CHEST

PAIN,and LUNG_CANCER. Gender is noted M for Male and F for Female, and Age is an integer and Lung_cancer is Yes/No. The remaining variables have a 2 which represents Yes and 1 which represents No.

 

1. Load the file into your Python environment (5pts)

2. For the variables with the 2/1 scores, replace all the 2 with a Yes and 1 with a No. (15pts)

3. Let’s categorize the AGE group as well. For all individuals less than 65 years old, assign them as “Middle” and all individuals greater than or equal to 65 as “Old”. (20pts)

4. Use a bar plot to show whether smokers have a higher probability of of getting cancer.

a. Do the same for alcohol drinking (20pts)

5. Randomly split the data into 20% testing and 80% training.(10pts)

6. Perform 5x cross validation on training ONLY.(10pts)

7. Test your model on the 20% test data.(10pts)

8. Compare and discuss the results from cross validation and the your final test. How confident are you that it will correctly predict new data? (10pts)

 

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