#split data training # https://en.wikipedia.org/wiki/Iris_flower_data_set #https://scikit-learn.org/stable/modules/model_evaluation.html?highlight=classification #evaluasi dengan pendekatan pembagian seimbang import sklearn from sklearn import datasets from sklearn.neighbors import KNeighborsClassifier from sklearn import model_selection #tambahani prediksi from sklearn.metrics import accuracy_score iris = datasets.load_iris() X =iris.data Y =iris.target kfold= model_selection.KFold (n_splits=10, random_state=14, shuffle=True) model = KNeighborsClassifier(n_neighbors=5) result= model_selection.cross_val_score(model, X, Y, cv=kfold,scoring='accuracy') print (result.mean(),result.std())
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