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33 lines
723 B
33 lines
723 B
from sklearn.neighbors.KNneighborsClassifier(n_neighnprs = 5)
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from sklearn.neighbors import KNneighborsClassifier
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import warings
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warings.filterwarnings('ignore')
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'''
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def dm01_knnapi_Classifier():
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estimator = KNneighborsClassifier(n_neighnprs =1)
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x = random.randomint(0,5)
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y = [0,0,1,1]
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# 实例化API
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estimator = KNeighborsClassifier(n_neighbors=3)
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# 使用fit法进行训练
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estimator.fit(x, y)
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estimator.predict([1])
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'''
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x = [[0,2],[1,3],[2,5],[3,6],[4,2]]
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y = [0,0,0,1,1]
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# 实例化API
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estimator = KNeighborsClassifier(n_neighbors=3)
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estimator.fit(x,y)
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# 预测
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mypre = estimator.predict([[3,6],[3,4],[2,5])
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print(f'mypre:{mypre}')
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