create a new svm$.$SVC$()$ object and assign it to the variable clf$1$ a call to svm$.$SVC$()$ creates a Support Vector Classifier from the svm submodule, similar to what we did in the earlier exercise on hand$-$written digits

call the fit method on clf$1$ with the x and y training data $($i$.$e$.,$ training the model to associate x$\_$train with y$\_$train$)$

call the predict method on clf$1$ on the x testing data and assign the result to the variable predictions$1,$ in order to make predictions for those inputs

call the accuracy$\_$score function on the y testing data and the test predictions you generated and assign the result to the variable score$1$

print the value of score$1$