03-myiris.py

#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())