# -*- coding: utf-8 -*-
"""securecyphercreditcardanalysis.space

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1WKtvyEIBM5bPAPOmwXTGkEAp8mSFNKii
"""

import numpy as np
import pandas as pd

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
  for filename in filenames:
    print(os.path.join(dirname, filename))

import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.svm import SVC
from sklearn.metrics import classification_report, confusion_matrix
import joblib
import matplotlib.pyplot as plt

input = pd.read_csv('/content/credit_card_fraud_synthetic.csv')

data = input.drop(['Timestamp', 'Transaction_Type', 'Location', 'Transaction_ID'], axis = 1)

data

y = data['Is_Fraudulent']
x = data.drop('Is_Fraudulent', axis = 1)
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=42)

svm_model = SVC(kernel='rbf')
svm_model.fit(X_train, y_train)

y_pred = svm_model.predict(X_test)

print("Confusion Matrix:")
print(confusion_matrix(y_test, y_pred))

print("Classification Report:")
print(classification_report(y_test, y_pred))

from sklearn.metrics import accuracy_score
Accu = accuracy_score(y_test, y_pred)
Accu = Accu * 100
print("The Accuracy of the model is ", round(Accu, 2), "%")