3. An Introduction to Classification

Activity 3.01: Increasing the Accuracy of Credit Scoring

Solution:

1. Open a new Jupyter Notebook file and execute all the steps from the previous exercise, Exercise 3.04, K-Nearest Neighbors Classification in Scikit-Learn.
2. Import neighbors from sklearn:

   from sklearn import neighbors

3. Create a function called fit_knn that takes the following parameters: k, p, features_train, label_train, features_test, and label_test. This function will fit KNeighborsClassifier with the training set and print the accuracy score for the training and testing sets, as shown in the following code snippet:

   def fit_knn(k, p, features_train, label_train, \
               features_test, label_test):
       classifier = neighbors.KNeighborsClassifier(n_neighbors=k, p=p)
       classifier.fit(features_train, label_train)
       return classifier.score...