perf metrix for classification based algo.py

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

from sklearn.datasets import load_iris
dataset = load_iris()


X = dataset.data
y = dataset.target

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y)

from sklearn.linear_model import LogisticRegression
log_reg = LogisticRegression()
log_reg.fit(X_train, y_train)

y_pred = log_reg.predict(X_test)

log_reg.score(X_train, y_train)
log_reg.score(X_test, y_test)
log_reg.score(X,y)

from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test, y_pred) 

from sklearn.metrics import precision_score, recall_score, f1_score
precision_score(y_test, y_pred, average = "macro")
recall_score(y_test, y_pred, average = "macro")
f1_score(y_test, y_pred, average = "macro")