Let's start with the simple and beautiful nearest neighbor method from the previous chapter. Although it is not as advanced as other methods, it is very powerful: as it is not model-based, it can learn nearly any data. But this beauty comes with a clear disadvantage, which we will find out very soon.
This time, we won't implement it ourselves, but rather take it from the
sklearn toolkit. There, the classifier resides in
sklearn.neighbors. Let's start with a simple 2-Nearest Neighbor classifier:
>>> from sklearn import neighbors >>> knn = neighbors.KNeighborsClassifier(n_neighbors=2) >>> print(knn) KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', n_neighbors=2, p=2, weights='uniform') ...