k-Nearest Neighbors: Fit

In this exercise, you will build your first classification model using the churn_df dataset, which has been preloaded for the remainder of the chapter.

The features to use will be "account_length" and "customer_service_calls". The target, "churn", needs to be a single column with the same number of observations as the feature data.

You will convert the features and the target variable into NumPy arrays, create an instance of a KNN classifier, and then fit it to the data.

numpy has also been preloaded for you as np.

Import KNeighborsClassifier from sklearn.neighbors.
Create an array called X containing values from the "account_length" and "customer_service_calls" columns, and an array called y for the values of the "churn" column.
Instantiate a KNeighborsClassifier called knn with 6 neighbors.
Fit the classifier to the data using the .fit() method.

Exercise

k-Nearest Neighbors: Fit

Instructions