Create fraud_detection_model.py

fraud_detection/fraud_detection_model.py

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+import numpy as np
+import pandas as pd
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import train_test_split
+
+class FraudDetectionModel:
+    def __init__(self, data):
+        self.data = data
+        self.X = self.data.drop('fraudulent', axis=1)
+        self.y = self.data['fraudulent']
+
+    def train_model(self):
+        X_train, X_test, y_train, y_test = train_test_split(self.X, self.y, test_size=0.2, random_state=42)
+        self.model = RandomForestClassifier(n_estimators=100, random_state=42)
+        self.model.fit(X_train, y_train)
+
+    def predict_fraud(self, new_data):
+        return self.model.predict(new_data)