Assume that you are given a data set and a neural network model trained on the data set. You are asked to build a decision tree model with the sole purpose of understanding/interpreting the built neural network model. In such a scenario, which among the following measures would you concentrate most on optimising?

A. accuracy of the decision tree model on the given data set

B. f1 measure of the decision tree model on the given data set

C. fidelity of the decision tree model, which is the fraction of instances on which the neural network and the decision tree give the same output

D. comprehensibility of the decision tree model, measured in terms of the size of the corresponding rule set

Answer: Option C

Solution(By Examveda Team)

In this scenario, the primary goal is to understand or interpret the neural network model using a decision tree. Fidelity measures how faithfully the decision tree model represents the behavior of the neural network model. It calculates the fraction of instances on which both models provide the same output. Therefore, optimizing Option C ensures that the decision tree model accurately reflects the predictions of the neural network model, aiding in its interpretation.