Как использовать ИИ для анализа данных — Создание собственных функций анализа

import pandas as pd

from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report

df = pd.read_csv("customers.csv")
X = df[["age", "income", "visit_count"]]
y = df["churn"]

X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42, stratify=y
)

model = RandomForestClassifier(n_estimators=100, random_state=42)
model.fit(X_train, y_train)
predictions = model.predict(X_test)

print(classification_report(y_test, predictions))