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from sklearn import datasets | |
from sklearn.neighbors import KNeighborsClassifier | |
# Load iris dataset from sklearn | |
iris = datasets.load_iris() | |
# Declare an of the KNN classifier class with the value with neighbors. | |
knn = KNeighborsClassifier(n_neighbors=6) | |
# Fit the model with training data and target values | |
knn.fit(iris['data'], iris['target']) | |
# Provide data whose class labels are to be predicted | |
X = [ | |
[5.9, 1.0, 5.1, 1.8], | |
[3.4, 2.0, 1.1, 4.8], | |
] | |
# Prints the data provided | |
print(X) | |
# Store predicted class labels of X | |
prediction = knn.predict(X) | |
# Prints the predicted class labels of X | |
print(prediction) |
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