74 You are building a ML model to predict whether houses for sale in a particular neighbour- hood will be sold in the next month or not. You have a dataset of 10,000 houses, their sale prices, date of purchase and other relevant attributes. (a) What will be your training- test data set split? [1] (b) You get 20,000 new samples as test data for your model evaluation. You notice that your model correctly predicts Yes 70% of the time and correctly predicts No, 30% of the time. If there are 18,000 actual YES samples in the dataset, compute the confusion matrix, Type I errors and Type II errors and accuracy. [3] (c) You tune hyper-parameters for your model and get the following ROC curve. Identify the parameter configuration (1, 2, 3 or 4) will you choose and justify the choice. [1]