5.2) [11 points] For this question, you are interested in modelling customer response to food deals offered luy different restaurants. The data shown in the table below lists 10 data points: the training data with labels. The first column in the table lists the deal id. The second column indicates the label, whether the user got the deal and ordered the food or not. The remaining three attributes describe the deals: Price Category specifies where the price level of the deal, Food type indicates whether the deal is on is Pizza or on Pide, Delivery speed indicates whether the restaurant's delivery speed is Fast or Slow. You will try to determine whether the customer will get the deal based on the attributes of the food deal (Price Category, Food type, Delivery Speed) by building a decision tree classifier. Deal id Ordered (Y) Price Category (X1) Food Type(X2) Delivery Speed(X;) 1 High Pide Slow Yes Txww Pizza Fast High Pizza Slow No Medium Pide Fast 5 Yes Low Piazza Slow No High Pide Slow Yes LOW Pide Slow Yes Medium Pizza Fast 9 Yes Medium Plaza Fast 10 No Medium Pide Fast No 2 No 6 7 8 Table 1: Deal order data. 5.2a) (4 pts.] What is the initial entropy of Ordered based on the training data? Show your work 5.2) [7 pts. Assume that Price Category is chosen for the root of the decision tree. What is the information gain associated with this attribute