import pandas as pd
from datasets import load_dataset
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier

# Load dataset
dataset = load_dataset("arun-gharami/lead-ai-fraud-detection-dataset")
df = dataset['train'].to_pandas()

# Features / Target
X = df.drop("fraud_label", axis=1)
y = df["fraud_label"]

# Train
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

model = RandomForestClassifier()
model.fit(X_train, y_train)

print("Model trained successfully 🚀")