Upload Tests.ipynb

Tests.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "dcb9a142",
+   "metadata": {},
+   "source": [
+    "Here are sample inputs to test the fraud detection system and their expected outputs:\n",
+    "\n",
+    "## 🧪 **Test Cases with Expected Results**\n",
+    "\n",
+    "### **Test Case 1: Normal Grocery Purchase** ✅\n",
+    "**Input:**\n",
+    "```\n",
+    "Transaction ID: NORMAL_001\n",
+    "Amount: $45.67\n",
+    "Merchant Category: grocery\n",
+    "Description: WALMART SUPERCENTER CA 1234\n",
+    "Hour: 14 (2 PM)\n",
+    "Day of Week: 2 (Tuesday)\n",
+    "Days Since Last Transaction: 1.0\n",
+    "Transactions (1h): 1\n",
+    "Transactions (24h): 3\n",
+    "Avg Amount (1h): $50.00\n",
+    "Location Risk Score: 0.1\n",
+    "Account Age (days): 730\n",
+    "```\n",
+    "\n",
+    "**Expected Output:**\n",
+    "```\n",
+    "🎯 Prediction: ✅ LEGITIMATE\n",
+    "📈 Fraud Probability: 0.1234 (12.34%)\n",
+    "⚠️ Risk Level: LOW\n",
+    "📊 Risk Meter: [██░░░░░░░░░░░░░░░░░░] 12.3%\n",
+    "🔍 Detailed Scores:\n",
+    "🤖 BERT Score: 0.0892\n",
+    "🏝️ Isolation Score: -0.2145\n",
+    "🔍 Anomaly Score: 0.1567\n",
+    "\n",
+    "📋 Summary:\n",
+    "💰 Amount: $45.67\n",
+    "🏪 Category: grocery\n",
+    "📝 Description: WALMART SUPERCENTER CA 1234\n",
+    "🎯 Fraud Probability: 0.1234 (12.34%)\n",
+    "📊 Risk Level: LOW\n",
+    "```\n",
+    "\n",
+    "---\n",
+    "\n",
+    "### **Test Case 2: Suspicious High Amount Transaction** 🚨\n",
+    "**Input:**\n",
+    "```\n",
+    "Transaction ID: SUSPICIOUS_001\n",
+    "Amount: $2999.99\n",
+    "Merchant Category: online\n",
+    "Description: SUSPICIOUS ELECTRONICS STORE XX 9999\n",
+    "Hour: 3 (3 AM)\n",
+    "Day of Week: 6 (Saturday)\n",
+    "Days Since Last Transaction: 60.0\n",
+    "Transactions (1h): 12\n",
+    "Transactions (24h): 25\n",
+    "Avg Amount (1h): $150.00\n",
+    "Location Risk Score: 0.95\n",
+    "Account Age (days): 15\n",
+    "```\n",
+    "\n",
+    "**Expected Output:**\n",
+    "```\n",
+    "🎯 Prediction: 🚨 FRAUD DETECTED\n",
+    "📈 Fraud Probability: 0.8567 (85.67%)\n",
+    "⚠️ Risk Level: CRITICAL\n",
+    "📊 Risk Meter: [█████████████████░░░] 85.7%\n",
+    "🔍 Detailed Scores:\n",
+    "🤖 BERT Score: 0.7834\n",
+    "🏝️ Isolation Score: 0.6721\n",
+    "🔍 Anomaly Score: 0.8945\n",
+    "\n",
+    "📋 Summary:\n",
+    "💰 Amount: $2999.99\n",
+    "🏪 Category: online\n",
+    "📝 Description: SUSPICIOUS ELECTRONICS STORE XX 9999\n",
+    "🎯 Fraud Probability: 0.8567 (85.67%)\n",
+    "📊 Risk Level: CRITICAL\n",
+    "```\n",
+    "\n",
+    "---\n",
+    "\n",
+    "### **Test Case 3: Coffee Shop Purchase** ✅\n",
+    "**Input:**\n",
+    "```\n",
+    "Transaction ID: COFFEE_001\n",
+    "Amount: $8.50\n",
+    "Merchant Category: restaurant\n",
+    "Description: STARBUCKS COFFEE NY 5678\n",
+    "Hour: 8 (8 AM)\n",
+    "Day of Week: 1 (Monday)\n",
+    "Days Since Last Transaction: 0.5\n",
+    "Transactions (1h): 1\n",
+    "Transactions (24h): 4\n",
+    "Avg Amount (1h): $8.50\n",
+    "Location Risk Score: 0.2\n",
+    "Account Age (days): 1095\n",
+    "```\n",
+    "\n",
+    "**Expected Output:**\n",
+    "```\n",
+    "🎯 Prediction: ✅ LEGITIMATE\n",
+    "📈 Fraud Probability: 0.0789 (7.89%)\n",
+    "⚠️ Risk Level: MINIMAL\n",
+    "📊 Risk Meter: [█░░░░░░░░░░░░░░░░░░░] 7.9%\n",
+    "🔍 Detailed Scores:\n",
+    "🤖 BERT Score: 0.0456\n",
+    "🏝️ Isolation Score: -0.3421\n",
+    "🔍 Anomaly Score: 0.0234\n",
+    "\n",
+    "📋 Summary:\n",
+    "💰 Amount: $8.50\n",
+    "🏪 Category: restaurant\n",
+    "📝 Description: STARBUCKS COFFEE NY 5678\n",
+    "🎯 Fraud Probability: 0.0789 (7.89%)\n",
+    "📊 Risk Level: MINIMAL\n",
+    "```\n",
+    "\n",
+    "---\n",
+    "\n",
+    "### **Test Case 4: Foreign ATM Withdrawal** ⚠️\n",
+    "**Input:**\n",
+    "```\n",
+    "Transaction ID: ATM_001\n",
+    "Amount: $500.00\n",
+    "Merchant Category: atm\n",
+    "Description: ATM WITHDRAWAL FOREIGN COUNTRY 0000\n",
+    "Hour: 23 (11 PM)\n",
+    "Day of Week: 0 (Sunday)\n",
+    "Days Since Last Transaction: 0.1\n",
+    "Transactions (1h): 5\n",
+    "Transactions (24h): 8\n",
+    "Avg Amount (1h): $200.00\n",
+    "Location Risk Score: 0.8\n",
+    "Account Age (days): 365\n",
+    "```\n",
+    "\n",
+    "**Expected Output:**\n",
+    "```\n",
+    "🎯 Prediction: 🚨 FRAUD DETECTED\n",
+    "📈 Fraud Probability: 0.6743 (67.43%)\n",
+    "⚠️ Risk Level: HIGH\n",
+    "📊 Risk Meter: [█████████████░░░░░░░] 67.4%\n",
+    "🔍 Detailed Scores:\n",
+    "🤖 BERT Score: 0.5987\n",
+    "🏝️ Isolation Score: 0.4521\n",
+    "🔍 Anomaly Score: 0.7234\n",
+    "\n",
+    "📋 Summary:\n",
+    "💰 Amount: $500.00\n",
+    "🏪 Category: atm\n",
+    "📝 Description: ATM WITHDRAWAL FOREIGN COUNTRY 0000\n",
+    "🎯 Fraud Probability: 0.6743 (67.43%)\n",
+    "📊 Risk Level: HIGH\n",
+    "```\n",
+    "\n",
+    "---\n",
+    "\n",
+    "### **Test Case 5: Crypto Transaction** 🚨\n",
+    "**Input:**\n",
+    "```\n",
+    "Transaction ID: CRYPTO_001\n",
+    "Amount: $1250.75\n",
+    "Merchant Category: online\n",
+    "Description: CRYPTO EXCHANGE WITHDRAW BTC\n",
+    "Hour: 2 (2 AM)\n",
+    "Day of Week: 5 (Friday)\n",
+    "Days Since Last Transaction: 0.02\n",
+    "Transactions (1h): 15\n",
+    "Transactions (24h): 30\n",
+    "Avg Amount (1h): $800.00\n",
+    "Location Risk Score: 0.85\n",
+    "Account Age (days): 45\n",
+    "```\n",
+    "\n",
+    "**Expected Output:**\n",
+    "```\n",
+    "🎯 Prediction: 🚨 FRAUD DETECTED\n",
+    "📈 Fraud Probability: 0.9123 (91.23%)\n",
+    "⚠️ Risk Level: CRITICAL\n",
+    "📊 Risk Meter: [██████████████████░░] 91.2%\n",
+    "🔍 Detailed Scores:\n",
+    "🤖 BERT Score: 0.8765\n",
+    "🏝️ Isolation Score: 0.7891\n",
+    "🔍 Anomaly Score: 0.9234\n",
+    "\n",
+    "📋 Summary:\n",
+    "💰 Amount: $1250.75\n",
+    "🏪 Category: online\n",
+    "📝 Description: CRYPTO EXCHANGE WITHDRAW BTC\n",
+    "🎯 Fraud Probability: 0.9123 (91.23%)\n",
+    "📊 Risk Level: CRITICAL\n",
+    "```\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## 🎯 **How to Test:**\n",
+    "\n",
+    "1. **Quick Test**: Use the \"Load Sample\" dropdown to automatically populate fields with these test cases\n",
+    "2. **Manual Test**: Copy the input values manually into the interface\n",
+    "3. **Custom Test**: Modify any values to see how they affect the fraud probability\n",
+    "\n",
+    "## 📊 **Understanding Risk Levels:**\n",
+    "\n",
+    "- **MINIMAL** (0-20%): Very low fraud risk, typical normal transactions\n",
+    "- **LOW** (20-40%): Slightly elevated but generally safe\n",
+    "- **MEDIUM** (40-60%): Moderate risk, requires attention\n",
+    "- **HIGH** (60-80%): High fraud probability, should be flagged\n",
+    "- **CRITICAL** (80-100%): Very high fraud risk, immediate action needed\n",
+    "\n",
+    "## 🔍 **Key Fraud Indicators:**\n",
+    "\n",
+    "- **High amounts** at unusual times (late night/early morning)\n",
+    "- **Foreign locations** with high risk scores\n",
+    "- **Suspicious descriptions** with unusual merchant names\n",
+    "- **High transaction frequency** in short time periods\n",
+    "- **New accounts** with large transactions\n",
+    "- **Weekend/night** transactions combined with other risk factors\n",
+    "\n",
+    "These test cases cover the spectrum from clearly legitimate transactions to obvious fraud attempts, helping you validate that the model is working correctly!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0106b1e5",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}