Complete the gaps in the following Python code, which is supposed to split the dataset into a training and test set, train a k-NN classifier, and evaluate its accuracy. data = Table.read_table("data.csv") = data.select("X1", "X2").values data.column("Y") X_train, X_test, y_train, y_test= train_test_split(x, y, train_size=0.7) knn_model= KNeighbors Classifier() knn_model.fit (X_train, y predicted = knn_model.predict (_ accuracy sum( = ) ) / len(_