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- #split data training
- # https://en.wikipedia.org/wiki/Iris_flower_data_set
- #https://scikit-learn.org/stable/modules/model_evaluation.html?highlight=classification
- #perbandingan model iris
- import sklearn
- from sklearn import datasets
- from sklearn.neighbors import KNeighborsClassifier
- from sklearn.naive_bayes import GaussianNB
- from sklearn.svm import SVC
- 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())
- model =GaussianNB()
- result= model_selection.cross_val_score(model, X, Y, cv=kfold,scoring='accuracy')
- print (result.mean(),result.std())
- model=SVC()
- result= model_selection.cross_val_score(model, X, Y, cv=kfold,scoring='accuracy')
- print (result.mean(),result.std())
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