fraud_detction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"CC.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.359807</td>\n",
       "      <td>-0.072781</td>\n",
       "      <td>2.536347</td>\n",
       "      <td>1.378155</td>\n",
       "      <td>-0.338321</td>\n",
       "      <td>0.462388</td>\n",
       "      <td>0.239599</td>\n",
       "      <td>0.098698</td>\n",
       "      <td>0.363787</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.018307</td>\n",
       "      <td>0.277838</td>\n",
       "      <td>-0.110474</td>\n",
       "      <td>0.066928</td>\n",
       "      <td>0.128539</td>\n",
       "      <td>-0.189115</td>\n",
       "      <td>0.133558</td>\n",
       "      <td>-0.021053</td>\n",
       "      <td>149.62</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.191857</td>\n",
       "      <td>0.266151</td>\n",
       "      <td>0.166480</td>\n",
       "      <td>0.448154</td>\n",
       "      <td>0.060018</td>\n",
       "      <td>-0.082361</td>\n",
       "      <td>-0.078803</td>\n",
       "      <td>0.085102</td>\n",
       "      <td>-0.255425</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.225775</td>\n",
       "      <td>-0.638672</td>\n",
       "      <td>0.101288</td>\n",
       "      <td>-0.339846</td>\n",
       "      <td>0.167170</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.008983</td>\n",
       "      <td>0.014724</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.358354</td>\n",
       "      <td>-1.340163</td>\n",
       "      <td>1.773209</td>\n",
       "      <td>0.379780</td>\n",
       "      <td>-0.503198</td>\n",
       "      <td>1.800499</td>\n",
       "      <td>0.791461</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>-1.514654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247998</td>\n",
       "      <td>0.771679</td>\n",
       "      <td>0.909412</td>\n",
       "      <td>-0.689281</td>\n",
       "      <td>-0.327642</td>\n",
       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\n",
       "      <td>378.66</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.966272</td>\n",
       "      <td>-0.185226</td>\n",
       "      <td>1.792993</td>\n",
       "      <td>-0.863291</td>\n",
       "      <td>-0.010309</td>\n",
       "      <td>1.247203</td>\n",
       "      <td>0.237609</td>\n",
       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.108300</td>\n",
       "      <td>0.005274</td>\n",
       "      <td>-0.190321</td>\n",
       "      <td>-1.175575</td>\n",
       "      <td>0.647376</td>\n",
       "      <td>-0.221929</td>\n",
       "      <td>0.062723</td>\n",
       "      <td>0.061458</td>\n",
       "      <td>123.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.158233</td>\n",
       "      <td>0.877737</td>\n",
       "      <td>1.548718</td>\n",
       "      <td>0.403034</td>\n",
       "      <td>-0.407193</td>\n",
       "      <td>0.095921</td>\n",
       "      <td>0.592941</td>\n",
       "      <td>-0.270533</td>\n",
       "      <td>0.817739</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009431</td>\n",
       "      <td>0.798278</td>\n",
       "      <td>-0.137458</td>\n",
       "      <td>0.141267</td>\n",
       "      <td>-0.206010</td>\n",
       "      <td>0.502292</td>\n",
       "      <td>0.219422</td>\n",
       "      <td>0.215153</td>\n",
       "      <td>69.99</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
       "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
       "0  0.098698  0.363787  ... -0.018307  0.277838 -0.110474  0.066928  0.128539   \n",
       "1  0.085102 -0.255425  ... -0.225775 -0.638672  0.101288 -0.339846  0.167170   \n",
       "2  0.247676 -1.514654  ...  0.247998  0.771679  0.909412 -0.689281 -0.327642   \n",
       "3  0.377436 -1.387024  ... -0.108300  0.005274 -0.190321 -1.175575  0.647376   \n",
       "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
       "\n",
       "        V26       V27       V28  Amount  Class  \n",
       "0 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.125895 -0.008983  0.014724    2.69      0  \n",
       "2 -0.139097 -0.055353 -0.059752  378.66      0  \n",
       "3 -0.221929  0.062723  0.061458  123.50      0  \n",
       "4  0.502292  0.219422  0.215153   69.99      0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "fraud = data.loc[data['Class']==1]  #for fraud\n",
    "normal = data.loc[data['Class']==0] #for no fraud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time      492\n",
       "V1        492\n",
       "V2        492\n",
       "V3        492\n",
       "V4        492\n",
       "V5        492\n",
       "V6        492\n",
       "V7        492\n",
       "V8        492\n",
       "V9        492\n",
       "V10       492\n",
       "V11       492\n",
       "V12       492\n",
       "V13       492\n",
       "V14       492\n",
       "V15       492\n",
       "V16       492\n",
       "V17       492\n",
       "V18       492\n",
       "V19       492\n",
       "V20       492\n",
       "V21       492\n",
       "V22       492\n",
       "V23       492\n",
       "V24       492\n",
       "V25       492\n",
       "V26       492\n",
       "V27       492\n",
       "V28       492\n",
       "Amount    492\n",
       "Class     492\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fraud.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "492"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fraud)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "284315"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(normal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x214b4502fa0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 558.875x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x = 'Amount', y = 'Time', hue='Class', data = data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x214b44f4b50>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FAgDQXoU0Zaf9+/erX79+kqRXXnlFN9xwgx577DFt27ZN119/fbMWCABAe9WkK2m3263i4mJJ0ltvvaVrr71WktSpUyf/FTYAADg3TbqSHjVqlNLT0zVy5Eht2bJFq1atkiR98sknuuCCC5q1QAAA2qsmXUkvWrRIISEhevnll/Xss8+qR48ekqS///3vGjt2bLMWCABAe+UwxphgF9GavF6voqOjVVBQoKioqGCXAwBAvZp0Jb1t2zbt2rXL//lf//pX3XzzzXrggQdUVlbWbMUBANCeNSmkf/rTn+qTTz6RJH3++ef64Q9/qIiICL300ku6//77m7VAAADaqyaF9CeffKLBgwdLkl566SWNGTNGK1as0PLly/XKK680Z30AALRbTQppY4x8Pp+kqiVY1WujExMTlZ+f33zVAQDQjjUppIcNG6ZHH31Uf/nLX/TOO+9o3Lhxkqp+yUl8fHyzFggAQHvVpJBeuHChtm3bpunTp+vBBx9UUlKSJOnll1/WlVde2awFAgDQXjXrEqySkhK5XC6FhoY215DNjiVYAIC2okm/caw+YWFhzTkcAADtWpNCurKyUr/97W/14osvKicnp9ba6GPHjjVLcQAAtGdN+pn0ww8/rKefflrjx49XQUGB0tPT9b3vfU9Op1Pz589v5hIBAGifmvQz6T59+ui///u/NW7cOHXs2FE7duzwt7333ntasWJFS9TaLPiZNACgrWjSlXRubq4GDBggSYqMjFRBQYEk6YYbbtDq1aubrzoAANqxJoX0BRdcoEOHDkmquqr+xz/+IUl6//335fF4mq86AADasSaF9C233KLMzExJ0owZMzRnzhwlJydr4sSJuuuuu5q1QAAA2qtmWSedlZWlrKwsJScn68Ybb2yOuloMP5MGALQV/D1pAAAs1eh10n/7298aPehNN93UpGIAAMA3Gn0l7XQ27sfXDodDlZWV51RUS+JKGgDQVjT6Srr6T1MCAIDWcVZ3d69bt079+vWT1+utta2goECXXXaZNmzY0GzFAQDQnp1VSC9cuFB33313nW8TR0dH66c//amefvrpZisOAID27KxC+sMPP9TYsWPr3X7ttddq69at51wUAAA4y5DOy8tr8G9Fh4SE6MiRI+dcFAAAOMuQ7tGjh3bv3l3v9p07d6pbt27nXBQAADjLkL7++us1Z84clZSU1Np26tQpzZs3TzfccEOzFQcAQHt2Vr9xLC8vT5dffrlcLpemT5+uvn37SpL27t2rxYsXq7KyUtu2bVN8fHyLFXyuWCcNAGgrzvrXgn7xxReaOnWq3nzzTVXv6nA4lJaWpsWLF6t3794tUmhzIaQBAG1Fk3939/Hjx5WdnS1jjJKTkxUbG9vctbUIQhoA0FbwBzYAALBUk/6eNAAAaHmENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApK0J68eLF6tWrl8LCwpSSkqItW7Y0ar+VK1fK4XDo5ptvbtkCAQAIgqCH9KpVq5Senq558+Zp27ZtGjRokNLS0nT48OEG9ztw4IB+9atfafTo0a1UKQAArcthjDHBLCAlJUVXXHGFFi1aJEny+XxKTEzUjBkzNGvWrDr3qays1JgxY3TXXXdpw4YNOnHihF5//fU6+5aWlqq0tNT/udfrVWJiogoKChQVFdXs5wMAQHMJ6pV0WVmZtm7dqtTUVH+b0+lUamqqsrKy6t3v17/+tbp27aopU6ac8RgZGRmKjo72PxITE5uldgAAWlpQQzo/P1+VlZWKj48PaI+Pj1dubm6d+2zcuFFLly7Vc88916hjzJ49WwUFBf7HwYMHz7luAABaQ0iwCzgbhYWFuuOOO/Tcc88pLi6uUft4PB55PJ4WrgwAgOYX1JCOi4uTy+VSXl5eQHteXp4SEhJq9f/ss8904MAB3Xjjjf42n88nSQoJCdG+ffvUp0+fli0aAIBWEtS3u91ut4YOHarMzEx/m8/nU2ZmpkaMGFGr/yWXXKJdu3Zpx44d/sdNN92kq666Sjt27ODnzQCA80rQ3+5OT0/XpEmTNGzYMA0fPlwLFy5UUVGRJk+eLEmaOHGievTooYyMDIWFhal///4B+8fExEhSrXYAANq6oIf0+PHjdeTIEc2dO1e5ubkaPHiw1q5d67+ZLCcnR05n0JdzAwDQ6oK+Trq1eb1eRUdHs04aAGA9LlEBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApQhoAAEsR0gAAWIqQBgDAUoQ0AACWIqQBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApQhoAAEsR0gAAWIqQBgDAUoQ0AACWIqQBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApawI6cWLF6tXr14KCwtTSkqKtmzZUm/f5557TqNHj1ZsbKxiY2OVmpraYH8AANqqoIf0qlWrlJ6ernnz5mnbtm0aNGiQ0tLSdPjw4Tr7r1+/XrfddpvefvttZWVlKTExUddee62+/PLLVq4cAICW5TDGmGAWkJKSoiuuuEKLFi2SJPl8PiUmJmrGjBmaNWvWGfevrKxUbGysFi1apIkTJ56xv9frVXR0tAoKChQVFXXO9QMA0FKCeiVdVlamrVu3KjU11d/mdDqVmpqqrKysRo1RXFys8vJyderUqc7tpaWl8nq9AQ8AANqCoIZ0fn6+KisrFR8fH9AeHx+v3NzcRo0xc+ZMde/ePSDoa8rIyFB0dLT/kZiYeM51AwDQGoL+M+lzsWDBAq1cuVKvvfaawsLC6uwze/ZsFRQU+B8HDx5s5SoBAGiakGAePC4uTi6XS3l5eQHteXl5SkhIaHDf3/zmN1qwYIHeeustDRw4sN5+Ho9HHo+nWeoFAKA1BfVK2u12a+jQocrMzPS3+Xw+ZWZmasSIEfXu98QTT+iRRx7R2rVrNWzYsNYoFQCAVhfUK2lJSk9P16RJkzRs2DANHz5cCxcuVFFRkSZPnixJmjhxonr06KGMjAxJ0uOPP665c+dqxYoV6tWrl/9n15GRkYqMjAzaeQAA0NyCHtLjx4/XkSNHNHfuXOXm5mrw4MFau3at/2aynJwcOZ3fXPA/++yzKisr0/e///2AcebNm6f58+e3ZukAALSooK+Tbm2skwYAtBVt+u5uAADOZ4Q0AACWIqQBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApQhoAAEsR0gAAWIqQBgDAUoQ0AACWIqQBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApQhoAAEsR0gAAWIqQBgDAUoQ0AACWIqQBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwFCENAIClCGkAACxFSAMAYClCGgAASxHSAABYipAGAMBShDQAAJYKCXYBbdWXx4tVWFqhwlMVigxzqYM7RKfKK3WypEKRYSFyhzjlMJLL6dCpikp5T1WogydEDklOpyQjySGFOJ06XlSmyLAQhYU45XQ4dLLsm3GcDsnhkMJCXDpeVKqOYW6VVfp0srRCHcNCFOpy6ujJUkWGhaqD26VSX6U8TpdKKitlfJLPSEWlVWN5XE6VVvpUeKpCHTwuhYW45HRUnU9ppU8+IxWXVqhTB7fKfVWfmxr7S5IxRmEhLrmdDpX5jIrLK1VcWqmOYSHyhDrlkFRa4fMft2NYiNwup44WlSnC7VJ4aNUxSyt98vmkwpKq+Yt0h6i4vHqeqvqFOh3yllaoqLRSUeEhigh1qbiiUqdKKxTbwaPScp+8JeWK9ITIE+JUWaVPRlX/8/RJ/vMMD3Up0lP1nBwuLNWJU+VV9bqcOlZUpvCv65JDKin36WRJhaLCQxQT4VZYiFP5J8tUcKpMEZ4QOR0OhTgd6tzBregItyQpz1ui40Vl8n69X2yEW/FRYWf19VRQXKb8k2U6WVqumAi3yiqqnuOo8FDF1ThWc6g+VkPn1NgxvCXlLVJje3e288vz0fKCNccOY4xp8aOcweLFi/Xkk08qNzdXgwYN0jPPPKPhw4fX2/+ll17SnDlzdODAASUnJ+vxxx/X9ddf36hjeb1eRUdHq6CgQFFRUU2q94ujRXrotV3akH1UEW6X/vu2IXp+035tyj7q7zM6OU4zrk6WQ0bREW5NeO495Z8s08ikzpo8srdWbsnRj751of6cdUATUi7UrFd2atGEy7V43afaUGOcmv0fHHepHnnjY63be6TW9p+9sF2X94zRIzf315L12bprVB/9+o2PtOnrGhdNGKLnN+6vNfb0q5LkcjhkZDRtxXYtuHWgVmz+QhNSLqx1TtXHem3rv/XLay/WvL99FHjOSXGafnWSJKPJyz9QcVllrRqH9IzRjKuT5ZTRncs/kCT9/vbLtXTD5wG1jU6K039e1UdT/vTNOKOT4jRldG8ZI/1x4+f+Y0e4XVo6aZiWbvhcE751YZ3n+fBNl2nBmj16q465m/XKTj1z2xD9/u3sWjVMuypJd/3p/VrnsmpLjn793f4qr/Rp9mu7AuZhVFJnPXbLAPXs3KFRX09fnTilma/s1NYvjtf5tTQmOU4Lbh2o7jHhjRqvMcfa8Gm+v63mOT383f5nPE5dYzRnje3d2c4vz0fLC+YcBz2kV61apYkTJ2rJkiVKSUnRwoUL9dJLL2nfvn3q2rVrrf7/+te/NGbMGGVkZOiGG27QihUr9Pjjj2vbtm3q37//GY93riH97+PFmv3KTv+L+fSrk7Q953jAi2q10Ulxun5AgiSpa1SYpvypKpRGJnXWkJ6x+jDnhAb1jNH2nOO6a2RvLTvtxbladf8dOcc1uGesFq3LrnP7onXZGpXUWfNuukzzawTo9KuTtCPnuDbWM/a4Ad0kSfFRYVq2ab+G9Iyt95xGJnVusNbRSZ113YBu+qqgJKDOmjVWH/OrghJJ0oc5xwPCsa59as7pdQMS9MBru/1t1c9B9RzVdZ6jkjrXO3eNmfu6zqVHTLjW7PyqztpHJXXWUz8YfMYr6oLiMk1/Ybs2fJrf4NfSmOQ4PXPbkHP6n3vNY52u+px2HjzR4HEaGqM5amzvznZ+eT5aXrDnOOg/k3766ad19913a/LkyerXr5+WLFmiiIgILVu2rM7+v/vd7zR27Fjdd999uvTSS/XII4/o8ssv16JFi+rsX1paKq/XG/A4F4UlFQEvykMSY+p8UZWkDdn56hoV9vXD42/flH1UQxJjtCE7379/1yhPveNU99/49b/1bZekjdlHVVFpAsaq3re+seOjwhT/dY3VYzVUS0O1bvh6vNPrrFnjphp9quah4fMOHD+/VvBV19vQeTY0d42Z+7raunb01Fv7xuyjOl5UVue2mvJPlvm/+Rua93c/zVf+yTOP19hjna76nM50nIbGaI4a27uznV+ej5YX7DkOakiXlZVp69atSk1N9bc5nU6lpqYqKyurzn2ysrIC+ktSWlpavf0zMjIUHR3tfyQmJp5Tzd5T5QGfl1b4GuxfWuFTaYVPJ0sq69yv+t/Tt9c1TkPHq9leeI41nql/Y2qta4yabdV9GlPbmdrONDcNjSU1fu5PbzvT8bwlFQ1ur+rzzXN1pvEKS8ob3H42x6pL9fEbOs6ZxjjXGtu7s51fno+WF+w5DmpI5+fnq7KyUvHx8QHt8fHxys3NrXOf3Nzcs+o/e/ZsFRQU+B8HDx48p5qjwkMDPveENDyFnhCnPCFORYa56tyv+t/Tt9c1TkPHq9ne8RxrPFP/xtRa1xg126r7NKa2M7WdaW4aGktq/Nyf3nam40WFnfm+zKiwb56rM43XMSy0we1nc6y6VB+/oeOcaYxzrbG9O9v55floecGe46C/3d3SPB6PoqKiAh7nomNYiEYnxfk/337whEYmda6z7+ikOB32lnz9KPW3j0zqrO0HT2h0Upx//8Pe0nrHqe4/6ut/69suVf0sNMTl0KgaY1Udq/6x87wlyvu6xuqxGqrlsLc0YPzAc64a7/Q6a9Y4skaf6nlo6LwDx49TnrckoK263obOs6G5a8zc19V2uLC0wePFdjjzz6niIt0akxwXcB51GZMcp7jIc/u5V81jna76nM50nIbGaI4a27uznV+ej5YX7DkOakjHxcXJ5XIpLy8voD0vL08JCQl17pOQkHBW/ZvbBbERevSW/hr99ZO2bON+TR7Zu1ZojU6O04xrkpXUNVLDenfSzFd2SvrmTtq9h7yaMrq3Pv6qQJNH9tbMV3ZqxtXJ/nGr1ez/yM0D9PFXBXVuX7Zxv0YlddYjNw/QH9/9THNuuMz/gr9s435NHtW7VhhW3d2drKQukerTJVIzX9mpySO/qen0wKg+1qtb/635N/Wvtb3q7u5k9ekSqWUb99dZ48ikzppxddUxl23cr2Ub92vK6N61znt0UpymX5UcME713d3dosMDjr1s435NvypJe7/y1nue82+6THsPeWu1V8/99KuSau03OqnqDv26zmXfIa+uuriL/uuWAbWe++q7uxuzDCs6wq0Ftw7UmOQ4/9fS6fM6JjlOj9868JxvTql5rJpqntOZjlPfGM1VY3t3tvPL89Hygj3HQb+7OyUlRcOHD9czzzwjSfL5fOrZs6emT5+uWbNm1eo/fvx4FRcX6//9v//nb7vyyis1cOBALVmy5IzHa44lWFLtddIR7hCVfL1OukNY1brd+tZJO5ySw0jGIYU6nTpeXKZIT9U6aYfDoaLT1knLIYWHuHS8uFSRHrfKT1snfayoVB08X6+TrqyUx1XPOukQp0orfCosqVCEu2qdtOv0ddJlFYqNcKvi9HXSnhDJUf866ep13g5H3eukjxWVKcztUsTp66RLKxTpCVwnHeGp6ldznXTH8BB18K+TrlRshFulFfWsk3ZUnXdhjbFqrpMuOPXNPjXr8q+T/rru2IB10uWKcLvkcjrkamiddFiIYjs0fZ10UWm5osOr1sJXzV+o4iJbap10/efU2DEKS8pbpMb27mznl+ej5QVrjoMe0qtWrdKkSZP0hz/8QcOHD9fChQv14osvau/evYqPj9fEiRPVo0cPZWRkSKpagvXtb39bCxYs0Lhx47Ry5Uo99thjrbYECwCA1hL03zg2fvx4HTlyRHPnzlVubq4GDx6stWvX+m8Oy8nJkdP5zbvyV155pVasWKGHHnpIDzzwgJKTk/X66683KqABAGhLgn4l3dq4kgYAtBXn/d3dAAC0VYQ0AACWIqQBALAUIQ0AgKUIaQAALEVIAwBgKUIaAABLEdIAAFiKkAYAwFKENAAAliKkAQCwVND/wEZrq/5V5V6v9ww9AQBoWR07dpTD4ah3e7sL6cLCQklSYmJikCsBALR3Z/pjT+3ur2D5fD599dVXZ/zfS2N4vV4lJibq4MGD/EWtBjBPjcM8NR5z1TjMU+MEc564kj6N0+nUBRdc0KxjRkVF8Q3QCMxT4zBPjcdcNQ7z1Dg2zhM3jgEAYClCGgAASxHS58Dj8WjevHnyeDzBLsVqzFPjME+Nx1w1DvPUODbPU7u7cQwAgLaCK2kAACxFSAMAYClCGgAASxHSAABYipA+B4sXL1avXr0UFhamlJQUbdmyJdgltZj58+fL4XAEPC655BL/9pKSEk2bNk2dO3dWZGSkbr31VuXl5QWMkZOTo3HjxikiIkJdu3bVfffdp4qKioA+69ev1+WXXy6Px6OkpCQtX768NU6vyd59913deOON6t69uxwOh15//fWA7cYYzZ07V926dVN4eLhSU1P16aefBvQ5duyYbr/9dkVFRSkmJkZTpkzRyZMnA/rs3LlTo0ePVlhYmBITE/XEE0/UquWll17SJZdcorCwMA0YMEBr1qxp9vNtqjPN05133lnr62vs2LEBfdrDPGVkZOiKK65Qx44d1bVrV918883at29fQJ/W/F6z9TWuMfP0ne98p9bX1D333BPQp03Mk0GTrFy50rjdbrNs2TLz0UcfmbvvvtvExMSYvLy8YJfWIubNm2cuu+wyc+jQIf/jyJEj/u333HOPSUxMNJmZmeaDDz4w3/rWt8yVV17p315RUWH69+9vUlNTzfbt282aNWtMXFycmT17tr/P559/biIiIkx6err5+OOPzTPPPGNcLpdZu3Ztq57r2VizZo158MEHzauvvmokmddeey1g+4IFC0x0dLR5/fXXzYcffmhuuukm07t3b3Pq1Cl/n7Fjx5pBgwaZ9957z2zYsMEkJSWZ2267zb+9oKDAxMfHm9tvv93s3r3bvPDCCyY8PNz84Q9/8PfZtGmTcblc5oknnjAff/yxeeihh0xoaKjZtWtXi89BY5xpniZNmmTGjh0b8PV17NixgD7tYZ7S0tLM888/b3bv3m127Nhhrr/+etOzZ09z8uRJf5/W+l6z+TWuMfP07W9/29x9990BX1MFBQX+7W1lngjpJho+fLiZNm2a//PKykrTvXt3k5GREcSqWs68efPMoEGD6tx24sQJExoaal566SV/2549e4wkk5WVZYypepF2Op0mNzfX3+fZZ581UVFRprS01BhjzP33328uu+yygLHHjx9v0tLSmvlsWsbp4ePz+UxCQoJ58skn/W0nTpwwHo/HvPDCC8YYYz7++GMjybz//vv+Pn//+9+Nw+EwX375pTHGmN///vcmNjbWP0/GGDNz5kzTt29f/+c/+MEPzLhx4wLqSUlJMT/96U+b9RybQ30h/d3vfrfefdrjPBljzOHDh40k88477xhjWvd7rS29xp0+T8ZUhfTPf/7zevdpK/PE291NUFZWpq1btyo1NdXf5nQ6lZqaqqysrCBW1rI+/fRTde/eXRdddJFuv/125eTkSJK2bt2q8vLygPm45JJL1LNnT/98ZGVlacCAAYqPj/f3SUtLk9fr1UcffeTvU3OM6j5tdU7379+v3NzcgHOKjo5WSkpKwLzExMRo2LBh/j6pqalyOp3avHmzv8+YMWPkdrv9fdLS0rRv3z4dP37c36etz9369evVtWtX9e3bV1OnTtXRo0f929rrPBUUFEiSOnXqJKn1vtfa2mvc6fNU7f/+7/8UFxen/v37a/bs2SouLvZvayvz1O7+wEZzyM/PV2VlZcCTK0nx8fHau3dvkKpqWSkpKVq+fLn69u2rQ4cO6eGHH9bo0aO1e/du5ebmyu12KyYmJmCf+Ph45ebmSpJyc3PrnK/qbQ318Xq9OnXqlMLDw1vo7FpG9XnVdU41z7lr164B20NCQtSpU6eAPr179641RvW22NjYeueuegzbjR07Vt/73vfUu3dvffbZZ3rggQd03XXXKSsrSy6Xq13Ok8/n0y9+8QuNHDlS/fv3l6RW+147fvx4m3mNq2ueJGnChAm68MIL1b17d+3cuVMzZ87Uvn379Oqrr0pqO/NESKNRrrvuOv/HAwcOVEpKii688EK9+OKLbS48YZ8f/vCH/o8HDBiggQMHqk+fPlq/fr2uueaaIFYWPNOmTdPu3bu1cePGYJditfrm6Sc/+Yn/4wEDBqhbt2665ppr9Nlnn6lPnz6tXWaT8XZ3E8TFxcnlctW6ozIvL08JCQlBqqp1xcTE6OKLL1Z2drYSEhJUVlamEydOBPSpOR8JCQl1zlf1tob6REVFtcn/CFSfV0NfJwkJCTp8+HDA9oqKCh07dqxZ5q6tfj1edNFFiouLU3Z2tqT2N0/Tp0/XG2+8obfffjvgT+u21vdaW3mNq2+e6pKSkiJJAV9TbWGeCOkmcLvdGjp0qDIzM/1tPp9PmZmZGjFiRBAraz0nT57UZ599pm7dumno0KEKDQ0NmI99+/YpJyfHPx8jRozQrl27Al5o//nPfyoqKkr9+vXz96k5RnWftjqnvXv3VkJCQsA5eb1ebd68OWBeTpw4oa1bt/r7rFu3Tj6fz/+iMmLECL377rsqLy/39/nnP/+pvn37KjY21t/nfJq7f//73zp69Ki6desmqf3MkzFG06dP12uvvaZ169bVevu+tb7XbH+NO9M81WXHjh2SFPA11SbmqVluP2uHVq5caTwej1m+fLn5+OOPzU9+8hMTExMTcKfg+eTee+8169evN/v37zebNm0yqampJi4uzhw+fNgYU7UspGfPnmbdunXmgw8+MCNGjDAjRozw71+93OHaa681O3bsMGvXrjVdunSpc7nDfffdZ/bs2WMWL15s/RKswsJCs337drN9+3YjyTz99NNm+/bt5osvvjDGVC3BiomJMX/961/Nzp07zXe/+906l2ANGTLEbN682WzcuNEkJycHLC06ceKEiY+PN3fccYfZvXu3WblypYmIiKi1tCgkJMT85je/MXv27DHz5s2zamlRQ/NUWFhofvWrX5msrCyzf/9+89Zbb5nLL7/cJCcnm5KSEv8Y7WGepk6daqKjo8369esDlg4VFxf7+7TW95rNr3Fnmqfs7Gzz61//2nzwwQdm//795q9//au56KKLzJgxY/xjtJV5IqTPwTPPPGN69uxp3G63GT58uHnvvfeCXVKLGT9+vOnWrZtxu92mR48eZvz48SY7O9u//dSpU+Y///M/TWxsrImIiDC33HKLOXToUMAYBw4cMNddd50JDw83cXFx5t577zXl5eUBfd5++20zePBg43a7zUUXXWSef/751ji9Jnv77beNpFqPSZMmGWOqlmHNmTPHxMfHG4/HY6655hqzb9++gDGOHj1qbrvtNhMZGWmioqLM5MmTTWFhYUCfDz/80IwaNcp4PB7To0cPs2DBglq1vPjii+biiy82brfbXHbZZWb16tUtdt5nq6F5Ki4uNtdee63p0qWLCQ0NNRdeeKG5++67a73ItYd5qmuOJAV8H7Tm95qtr3FnmqecnBwzZswY06lTJ+PxeExSUpK57777AtZJG9M25ok/VQkAgKX4mTQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApQhoAAEsR0gAAWIqQBgDAUoQ0AACWIqSB81D132EeN25csEs5K9/5znf0i1/8IthlANYgpIHz0NKlSzVjxgy9++67+uqrr4JdDoAmIqSB88zJkye1atUqTZ06VePGjdPy5cv929avXy+Hw6E333xTQ4YMUXh4uK6++modPnxYf//733XppZcqKipKEyZMUHFxsX+/0tJS/exnP1PXrl0VFhamUaNG6f333/dvX758uWJiYgLqeP311+VwOPyfz58/X4MHD9Zf/vIX9erVS9HR0frhD3+owsJCSdKdd96pd955R7/73e/kcDjkcDh04MCBFpkjoK0gpIHzzIsvvqhLLrlEffv21Y9+9CMtW7ZMp/8dnfnz52vRokX617/+pYMHD+oHP/iBFi5cqBUrVmj16tX6xz/+oWeeecbf//7779crr7yiP/3pT9q2bZuSkpKUlpamY8eOnVVtn332mV5//XW98cYbeuONN/TOO+9owYIFkqTf/e53GjFihO6++24dOnRIhw4dUmJi4rlPCNCGEdLAeWbp0qX60Y9+JEkaO3asCgoK9M477wT0efTRRzVy5EgNGTJEU6ZM0TvvvKNnn31WQ4YM0ejRo/X9739fb7/9tiSpqKhIzz77rJ588kldd9116tevn5577jmFh4dr6dKlZ1Wbz+fT8uXL1b9/f40ePVp33HGHMjMzJUnR0dFyu92KiIhQQkKCEhIS5HK5mmFGgLaLkAbOI/v27dOWLVt02223SZJCQkI0fvz4WmE6cOBA/8fx8fGKiIjQRRddFNB2+PBhSVVXv+Xl5Ro5cqR/e2hoqIYPH649e/acVX29evVSx44d/Z9369bNfxwAtYUEuwAAzWfp0qWqqKhQ9+7d/W3GGHk8Hi1atMjfFhoa6v/Y4XAEfF7d5vP5Gn1cp9NZ6y318vLyWv3O9ThAe8OVNHCeqKio0J///Gc99dRT2rFjh//x4Ycfqnv37nrhhReaNG6fPn3kdru1adMmf1t5ebnef/999evXT5LUpUsXFRYWqqioyN9nx44dZ30st9utysrKJtUJnI+4kgbOE2+88YaOHz+uKVOmKDo6OmDbrbfeqqVLl+rJJ58863E7dOigqVOn6r777lOnTp3Us2dPPfHEEyouLtaUKVMkSSkpKYqIiNADDzygn/3sZ9q8eXPAXeWN1atXL23evFkHDhxQZGSkOnXqJKeTawm0X3z1A+eJpUuXKjU1tVZAS1Uh/cEHH2jnzp1NGnvBggW69dZbdccdd+jyyy9Xdna23nzzTcXGxkqSOnXqpP/93//VmjVrNGDAAL3wwguaP3/+WR/nV7/6lVwul/r166cuXbooJyenSfUC5wuHOf0HSQAAwApcSQMAYClCGgAASxHSAABYipAGAMBShDQAAJYipAEAsBQhDQCApQhpAAAsRUgDAGApQhoAAEsR0gAAWOr/A0MSHxxWFkD6AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x = 'Amount', y = 'Class', data = data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import linear_model\n",
    "from sklearn.model_selection import train_test_split #used for selecting proper model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.iloc[:,:-1] #only the values\n",
    "y = data['Class']    #value of target variable Class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size=0.35)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = linear_model.LogisticRegression(C=1e5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\mekal\\AppData\\Local\\Programs\\Python\\Python38\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py:458: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "data": {
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      ],
      "text/plain": [
       "LogisticRegression(C=100000.0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred= np.array(clf.predict(X_test))\n",
    "y = np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix, classification_report, accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[99490    40]\n",
      " [   58    95]]\n"
     ]
    }
   ],
   "source": [
    "print(confusion_matrix(y, y_pred)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9990168835207608\n"
     ]
    }
   ],
   "source": [
    "print(accuracy_score(y, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00     99530\n",
      "           1       0.70      0.62      0.66       153\n",
      "\n",
      "    accuracy                           1.00     99683\n",
      "   macro avg       0.85      0.81      0.83     99683\n",
      "weighted avg       1.00      1.00      1.00     99683\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y, y_pred))"
   ]
  }
 ],
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