Answer:
import the GaussianNB class from the scikit-learn naive bayes module using the import statement;
from sklearn.naivebayes import GaussianNB
create the classifier,
clf = GaussianNB()
Then train or fit a section of the dataset (the training set) with the classifier, then predict the label of the test section of the dataset with the provided query "q".
trained = clf.fit( train_features, train_label)
predict = clf.predict(q)
Step-by-step explanation:
The scikit-learn is a machine learning package in python used to create machine models from datasets. It has several classifiers and regressions algorithms.
The naive baye algorithm is a machine learning class in python used in supervised machine learning to create models used to predict a label given a set of features using a classifier.