Scikit-learn Preliminary, a KNN algorithm example

1 ImportNumPy as NP2  fromSklearnImportDatasets#Data Set3  fromSklearn.model_selectionImportTrain_test_split#Train_test_split is used to divide data into training sets and test sets4  fromSklearn.neighborsImportKneighborsclassifier#inductive KNN algorithm5Iris = Datasets.load_iris ()#data from datasets to be loaded into Iris6Iris_x =Iris.data7Iris_y =Iris.target8X_train,x_test,y_train,y_test = Train_test_split (iris_x,iris_y,test_size=0.3)#split Training sets and test sets9KNN =Kneighborsclassifier ()TenKnn.fit (X_train,y_train)#Training

Make predictions with a well-trained KNN

1 Print # Print Forecast Results 2 Print # Print Real Results 3 [1 1 0 0 2 0 2 1 0 1 0 2 2 0 2 2 1 2 1 0 1 1 1 0 2 1 1 0 0 1 1 0 1 1 1 0 2 1 2 0 2 0 1 1 1]4 [1 1 0 0 2 0 2 1 0 1 0 2 2 0 2 2 2 2 1 0 1 1 1 0 2 1 1 0 0 1 1 0 1 1 1 0 2 1 2 0 1 0 1 1 1]

Scikit-learn Preliminary, a KNN algorithm example