A. If the decision tree is constructed using ID3 classifier with entropy based information gain as a criterion for attribute selection, Identify the attribute used at the root. Show all the calculations involved. Draw the resultant tree after the first iteration. B. Consider the decision trees given below in the table. Which of the trees is more suitable for the given data? Use precision of class = "High" and Recall of class="Medium" as the decision criteria and explain with necessary computations. High Low Decision Tree 1 Low Vertical Variance Horizontal Variance Low Medium High High Decision Tree 2 High High Vertical Variance High Low Medium ASM Low Horizontal Variance Low High Medium Low GLCM Horizontal Variance High High Low Low High High Low Low Low High High Low GLCM Vertical Variance High Low Low High Low Low Low Low High High High High ASM (or Energy) for Vertical GICM High Low Low Low High High Low Low Low High High Low Fruit Quality (Target) High Medium Low Low Medium High Medium Medium Low High Medium Medium Training Data Test Data