If the training set is such that every combination of attribute values is present in the training data and every combination is either labeled as positive or negative, which of the following classification techniques can be used to learn a model with perfect classification (zero errors) on the training set? Briefly explain your answer.

a. Decision Trees

b. Logistic Regression

c. Nave Bayes

d. Multi-layer ANN

e. Linear SVM