با استفاده از sklearn و یکی از مجموعه داده های آموزشی، یک مدل جنگل تصادفی ایجاد کنید.

import numpy as np import pandas as pd from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split from sklearn.datasets import load_iris

Load the iris dataset

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

Split the data into training and testing sets

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

Create a Random Forest Classifier model

rf_model = RandomForestClassifier(n_estimators=100, random_state=42)

Fit the model on the training data

rf_model.fit(X_train, y_train)

Evaluate the model

accuracy = rf_model.score(X_test, y_test) print("Random Forest Classifier Accuracy:", accuracy)