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Exercise

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 target, "churn", needs to be a single column with the same number of observations as the feature data. The feature data has already been converted into numpy arrays.

"account_length" and "customer_service_calls" are treated as features because account length indicates customer loyalty, and frequent customer service calls may signal dissatisfaction, both of which can be good predictors of churn.

Instructions

100 XP
  • Import KNeighborsClassifier from sklearn.neighbors.
  • Instantiate a KNeighborsClassifier called knn with 6 neighbors.
  • Fit the classifier to the data using the .fit() method.