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29 lines
707 B
Python
29 lines
707 B
Python
from sklearn.model_selection import train_test_split
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from sklearn.datasets import load_iris
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from sklearn.neighbors import KNeighborsClassifier
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#Load iris file
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iris = load_iris()
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iris.keys()
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print('Target names: \n {} '.format(iris.target_names))
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print('\n Features: \n {}'.format(iris.feature_names))
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#Train set e Test set
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X_train, X_test, y_train, y_test = train_test_split(iris['data'],iris['target'], random_state=4)
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#KNN
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knn = KNeighborsClassifier (n_neighbors = 1)
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knn.fit(X_train, y_train)
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#new array to test
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X_new = [[1,2,1,4],
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[2,3,4,5]]
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prediction = knn.predict(X_new)
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print('\nNew array: \n {}'
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'\n\nTarget Names Prediction: \n {}'.format(X_new, iris['target_names'][prediction]))
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