scikit-learn Cookbook , Second Edition - Second Edition

How to do it…

For this recipe, we'll use the iris dataset. If we want to predict something such as the petal width for each flower, clustering by iris species can potentially give us better results. The KNN regression won't cluster by the species, but we'll work under the assumption that the Xs will be close for the same species, in this case, the petal length:

1. We'll use the iris dataset for this recipe:

import numpy as npfrom sklearn import datasetsiris = datasets.load_iris()iris.feature_names

2. We'll try to predict the petal length based on the sepal length and width. We'll also fit a regular linear regression to see how well the KNN regression does in comparison:

 X = iris.data[:,:2] y = iris.data[:,2]  from sklearn.linear_model import ...