import numpy as np
import pandas as pd
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report

iris = datasets.load_iris()
X = iris.data
y = iris.target

Xtrain, Xtest, ytrain, ytest = train_test_split(X, y, test_size=0.3, random_state=42)

model = DecisionTreeClassifier()
model.fit(Xtrain, ytrain)

predictions = model.predict(Xtest)

accuracy = accuracy_score(y_test, predictions)
confusion = confusion_matrix(y_test, predictions)
report = classification_report(y_test, predictions)

print("Decision Tree Performance Metrics:")
print("Accuracy:", accuracy)
print("Confusion Matrix:\n", confusion)
print("Classification Report:\n", report)