step model evaluation after dividing the data into training and testing we need to build the model we will be using naive bayes algorithm for this purpose the following commands will import the gaussiannb modulefrom sklearn naive_bayes import gaussiannb nowinitialize the model as followsgnb gaussiannb(nextwith the help of following command we can train the modelmodel gnb fit(traintrain_labelsnowfor evaluation purpose we need to make predictions it can be done by using predict(function as followspreds gnb predict(testprint(predsthis will give the following output[ the above series of and in output are the predicted values for the malignant and benign tumor classes step finding accuracy we can find the accuracy of the model build in previous step by comparing the two arrays namely test_labels and preds we will be using the accuracy_score(function to determine the accuracy from sklearn metrics import accuracy_score print(accuracy_score(test_labels,preds) the above output shows that naivebayes classifier is accurate