from  sklearn.datasets  import load_iris
from  sklearn.model_selection import  train_test_split
from  sklearn.tree import  DecisionTreeClassifier
import  numpy as np

iris_dataset = load_iris()

X_train,X_test,y_train,y_test = train_test_split(iris_dataset.data,iris_dataset.target,random_state=0)

# print(y_test)


model = DecisionTreeClassifier()
mymodel = model.fit(X_train,y_train)

mymodel.predict(X_test)

X_New = np.array([[6.0,3.23,4.5,2.0]])
print(mymodel.predict(X_New))
print(mymodel.score(X_test,y_test))
