QUESTION 1 Match each statement with the corresponding classification technique A. Model is very easy to understand and interpret. Support Vector Machines B. Naive Bayes C Decision Trees D.k-Nearest Neighbors Provides probabilities that quantify the uncertainty in the predictions Produces decision boundaries of any shape. Produces rectilinear decision boundaries. Produces both linear and nonlinear decision boundaries Assumes that attributes are conditionally independent Training is computationally expensive. Testing is computationally expensive