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?

Question

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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

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accuracy of the decision tree model on the given data set

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

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

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