在python中利用KNN实现对iris进行分类的方法
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2022-10-18 12:37:38
如下所示:
from sklearn.datasets import load_iris
iris = load_iris()
print iri...
如下所示:
from sklearn.datasets import load_iris iris = load_iris() print iris.data.shape from sklearn.cross_validation import train_test_split x_train, x_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size = 0.25, random_state = 33) from sklearn.preprocessing import standardscaler from sklearn.neighbors import kneighborsclassifier ss = standardscaler() x_train = ss.fit_transform(x_train) x_test = ss.transform(x_test) knc = kneighborsclassifier() knc.fit(x_train, y_train) y_predict = knc.predict(x_test) print 'the accuracy of k-nearest neighbor classifier is: ', knc.score(x_test, y_test) from sklearn.metrics import classification_report print classification_report(y_test, y_predict, target_names = iris.target_names)
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