Problem 1: Linear Regression You are hired by a company Gem Stones co Itd, which is a cubic zirconia manufacturer. You are provided with the dataset containing the prices and other attributes of almost 27,000 cubic zirconia (which is an inexpensive diamond alternative with many of the same qualities as a diamond). The company is earning different profits on different prize slots. You have to help the company in predicting the price for the stone on the bases of the details given in the dataset so it can distinguish between higher profitable stones and lower profitable stones so as to have better profit share. Also, provide them with the best 5 attributes that are most important. Data Dictionary: Variable Name Description Carat Carat weight of the cubic zirconia. Cut Describe the cut quality of the cubic zirconia. Quality is increasing order Fair, Good, Very Good, Premium, Ideal. Color Colour of the cubic zirconia. With D being the best and J the worst. cubic zirconia Clarity refers to the absence of the Inclusions and Blemishes. (In Clarity order from Best to Worst, FL = flawless, 13= level 3 inclusions) FL, IF, VVS1, VV$2, VS1, VS2, SI1, $12, 11, 12, 13 The Height of a cubic zirconia, measured from the Culet to the table, divided by Depth its average Girdle Diameter. The Width of the cubic zirconia's Table expressed as a Percentage of its Average Table Diameter. Price the Price of the cubic zirconia. X Length of the cubic zirconia in mm. Y Width of the cubic zirconia in mm. Height of the cubic zirconia in mm