Task2: Linear regression: This is a dataset to predict the heath insurance costs of customers for a real health isurance company. Target variable is "charges" , For "sex", and "smoker" features, replace classes with 0 or 1. For instance "female" could be 0, "male" could be 1. Choice of 0 and 1 is oprional. You will use these to build the model ,, Use multiple linear regressionto predict charges. Set 20% of the data to be "test" set. Calculate RMSE for test set and training set. a) Calculate RMSE?

b) which feature better to be dropped? Compare first model and second model

c) which model is better

d) why

age	sex	bmi	children	smoker	charges
19	0	27.9	0	0	16884.92
18	1	33.77	1	1	1725.552
28	1	33	3	1	4449.462
33	1	22.705	0	1	21984.47
32	1	28.88	0	1	3866.855
31	0	25.74	0	1	3756.622
46	0	33.44	1	1	8240.59
37	0	27.74	3	1	7281.506
37	1	29.83	2	1	6406.411