SupervisedLearning_R3_Project2_TheraBank.ipynb

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   "cell_type": "markdown",
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    "id": "YXt7PB5VuHPj"
   },
   "source": [
    "## Project 2 for Supervised Learning\n",
    "\n",
    "*Please find below the Project 2 for Supervised Learning course.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "YW5BYFevuHPk"
   },
   "source": [
    "### Overview:\n",
    "\n",
    "1.\tRead the column description and ensure you understand each attribute well\n",
    "2.\tStudy the data distribution in each attribute, share your findings. (5 points)\n",
    "3.\tGet the target column distribution. Your comments\n",
    "4.\tSplit the data into training and test set in the ratio of 70:30 respectively\n",
    "5.\tUse different classification models (Logistic, K-NN and Naïve Bayes) to predict the likelihood of a liability customer buying personal loans (15 points)\n",
    "6.\tPrint the confusion matrix for all the above models (5 points)\n",
    "7.  Give your reasoning on which is the best model in this case and why it performs better? (5 points)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0gl2MdwkuHPl"
   },
   "source": [
    "## Problem Statement \n",
    "\n",
    "Campaign for selling personal loans.\n",
    "This case is about a bank (Thera Bank) which has a growing customer base. Majority of these customers are liability customers (depositors) with varying size of deposits. The number of customers who are also borrowers (asset customers) is quite small, and the bank is interested in expanding this base rapidly to bring in more loan business and in the process, earn more through the interest on loans. In particular, the management wants to explore ways of converting its liability customers to personal loan customers (while retaining them as depositors). A campaign that the bank ran last year for liability customers showed a healthy conversion rate of over 9% success. This has encouraged the retail marketing department to devise campaigns with better target marketing to increase the success ratio with minimal budget.\n",
    "\n",
    "The department wants to build a model that will help them identify the potential customers who have higher probability of purchasing the loan. This will increase the success ratio while at the same time reduce the cost of the campaign.\n",
    "\n",
    "The file Bank.xls contains data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer's relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.\n",
    "\n",
    "\n",
    "## Dataset \n",
    "\n",
    "Bank_Personal_Loan_Modelling-1.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cHpGO_AGuHPm"
   },
   "source": [
    "## Import the necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "q3YEgKevuHPn"
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "from sklearn import preprocessing\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read the column description and ensure you understand each attribute well"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KHyQrv_muHPr",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "customers = pd.read_csv('Data/Bank_Personal_Loan_Modelling-1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', 'Age', 'Experience', 'Income', 'ZIP Code', 'Family', 'CCAvg',\n",
       "       'Education', 'Mortgage', 'Personal Loan', 'Securities Account',\n",
       "       'CD Account', 'Online', 'CreditCard'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "      <th>Family</th>\n",
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       "      <th>Mortgage</th>\n",
       "      <th>Personal Loan</th>\n",
       "      <th>Securities Account</th>\n",
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       "      <th>CreditCard</th>\n",
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       "      <th>0</th>\n",
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       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "   ID  Age  Experience  Income  ZIP Code  Family  CCAvg  Education  Mortgage  \\\n",
       "0   1   25           1      49     91107       4    1.6          1         0   \n",
       "1   2   45          19      34     90089       3    1.5          1         0   \n",
       "2   3   39          15      11     94720       1    1.0          1         0   \n",
       "3   4   35           9     100     94112       1    2.7          2         0   \n",
       "4   5   35           8      45     91330       4    1.0          2         0   \n",
       "\n",
       "   Personal Loan  Securities Account  CD Account  Online  CreditCard  \n",
       "0              0                   1           0       0           0  \n",
       "1              0                   1           0       0           0  \n",
       "2              0                   0           0       0           0  \n",
       "3              0                   0           0       0           0  \n",
       "4              0                   0           0       0           1  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>2500.500000</td>\n",
       "      <td>1443.520003</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1250.75</td>\n",
       "      <td>2500.5</td>\n",
       "      <td>3750.25</td>\n",
       "      <td>5000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>45.338400</td>\n",
       "      <td>11.463166</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>45.0</td>\n",
       "      <td>55.00</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Experience</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>20.104600</td>\n",
       "      <td>11.467954</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>73.774200</td>\n",
       "      <td>46.033729</td>\n",
       "      <td>8.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>98.00</td>\n",
       "      <td>224.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZIP Code</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>93152.503000</td>\n",
       "      <td>2121.852197</td>\n",
       "      <td>9307.0</td>\n",
       "      <td>91911.00</td>\n",
       "      <td>93437.0</td>\n",
       "      <td>94608.00</td>\n",
       "      <td>96651.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Family</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>2.396400</td>\n",
       "      <td>1.147663</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCAvg</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.937938</td>\n",
       "      <td>1.747659</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.50</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.881000</td>\n",
       "      <td>0.839869</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mortgage</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>56.498800</td>\n",
       "      <td>101.713802</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>101.00</td>\n",
       "      <td>635.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Personal Loan</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.096000</td>\n",
       "      <td>0.294621</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Securities Account</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.104400</td>\n",
       "      <td>0.305809</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD Account</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.060400</td>\n",
       "      <td>0.238250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Online</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.596800</td>\n",
       "      <td>0.490589</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CreditCard</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>0.294000</td>\n",
       "      <td>0.455637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                     count          mean          std     min       25%  \\\n",
       "ID                  5000.0   2500.500000  1443.520003     1.0   1250.75   \n",
       "Age                 5000.0     45.338400    11.463166    23.0     35.00   \n",
       "Experience          5000.0     20.104600    11.467954    -3.0     10.00   \n",
       "Income              5000.0     73.774200    46.033729     8.0     39.00   \n",
       "ZIP Code            5000.0  93152.503000  2121.852197  9307.0  91911.00   \n",
       "Family              5000.0      2.396400     1.147663     1.0      1.00   \n",
       "CCAvg               5000.0      1.937938     1.747659     0.0      0.70   \n",
       "Education           5000.0      1.881000     0.839869     1.0      1.00   \n",
       "Mortgage            5000.0     56.498800   101.713802     0.0      0.00   \n",
       "Personal Loan       5000.0      0.096000     0.294621     0.0      0.00   \n",
       "Securities Account  5000.0      0.104400     0.305809     0.0      0.00   \n",
       "CD Account          5000.0      0.060400     0.238250     0.0      0.00   \n",
       "Online              5000.0      0.596800     0.490589     0.0      0.00   \n",
       "CreditCard          5000.0      0.294000     0.455637     0.0      0.00   \n",
       "\n",
       "                        50%       75%      max  \n",
       "ID                   2500.5   3750.25   5000.0  \n",
       "Age                    45.0     55.00     67.0  \n",
       "Experience             20.0     30.00     43.0  \n",
       "Income                 64.0     98.00    224.0  \n",
       "ZIP Code            93437.0  94608.00  96651.0  \n",
       "Family                  2.0      3.00      4.0  \n",
       "CCAvg                   1.5      2.50     10.0  \n",
       "Education               2.0      3.00      3.0  \n",
       "Mortgage                0.0    101.00    635.0  \n",
       "Personal Loan           0.0      0.00      1.0  \n",
       "Securities Account      0.0      0.00      1.0  \n",
       "CD Account              0.0      0.00      1.0  \n",
       "Online                  1.0      1.00      1.0  \n",
       "CreditCard              0.0      1.00      1.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observations of the data model:\n",
    "- ID and ZIP are nominal data and won't have any impact on the target feature\n",
    "- ZIP may have impact on the Personal Loan if we process that by OneHotEncoding but we will ignore in the given analysis\n",
    "- Age, Experience, Income, CCAvg and Mortgage are Continuous data\n",
    "- Family and Education are Categorical and Ordinal data\n",
    "- Securities Account, CD Account, Online, CreditCard and Personal Loan are Categorical and Binary data\n",
    "- Personal Loan is a target feature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Study the data distribution in each attribute, share your findings. (5 points)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleanup:\n",
    "\n",
    "#### 1. Null or NA values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                    False\n",
       "Age                   False\n",
       "Experience            False\n",
       "Income                False\n",
       "ZIP Code              False\n",
       "Family                False\n",
       "CCAvg                 False\n",
       "Education             False\n",
       "Mortgage              False\n",
       "Personal Loan         False\n",
       "Securities Account    False\n",
       "CD Account            False\n",
       "Online                False\n",
       "CreditCard            False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                    False\n",
       "Age                   False\n",
       "Experience            False\n",
       "Income                False\n",
       "ZIP Code              False\n",
       "Family                False\n",
       "CCAvg                 False\n",
       "Education             False\n",
       "Mortgage              False\n",
       "Personal Loan         False\n",
       "Securities Account    False\n",
       "CD Account            False\n",
       "Online                False\n",
       "CreditCard            False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.isna().any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 5000 entries in the dataset without NA or Null or missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. Negative values:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above describe() shows that Experience has Negative value. Finding out how many of them are Negative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    4948\n",
       "True       52\n",
       "Name: Experience, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(customers.Experience < 0).value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the given problem, it is safe to set Negative Experience values to 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting Negative columns to zero\n",
    "customers.loc[customers.Experience < 0, 'Experience'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    5000\n",
       "Name: Experience, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(customers.Experience < 0).value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ditributions: "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Continuous Variables: Age and Experience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf161128>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "customers.Age.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations$:\n",
    "    - Age seem to be normally distributed\n",
    "    - The variance of Age seemed to be high from the mean value\n",
    "    - Most of the customers seemed to be aged between 30 and 60"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf48add8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "customers.Experience.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations$:\n",
    "- Experience doesn't seem to have normal distribution\n",
    "- The variance seemed to be high from the mean value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf5146a0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=customers, x='Age', y='Experience', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations$:\n",
    "- Age and Experience are strongly correlated. It can be safer to consider to only one of them. The other won't have additional impact on the target variable.\n",
    "- Both of them don't seem to have much impact on whether the customer applied for the Personal Loan or not\n",
    "- Both of them can be excluded in the modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Education and Income:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf5c5828>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=customers, x='Education', y='Income', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observation:$\n",
    "- Proportion of customers who applied for Persoanl Loan are almost same with all education level.\n",
    "- So, Education may not have much impact on the target variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Family and Income:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf6b0da0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=customers, x='Family', y='Income', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observation:$\n",
    "- Proportion of customers who applied for Persoanl Loan are almost same with number of Family members\n",
    "- So, Family members may not have much impact on the target variable\n",
    "- Customers who applied for Personal Loan seemed to have higher Income than who didn't apply\n",
    "- So, Income seemed to be impacting the target variable and so should be included in the modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Mortgage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf799400>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=customers, x='Family', y='Mortgage', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations:$\n",
    "    - Customers who applied for Personal Loan have high Mortgage than who didn't apply for Persoanl Loan\n",
    "    - Mortgage amount seemed to high impact on the target variable and so should be included in the modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### CCAvg and CreditCard:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf8655f8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=customers, x='CreditCard', y='CCAvg', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations:$\n",
    "- Customers who applied for Personal Loan seemed to have high Credit Card spending than who didn't apply\n",
    "- Credit Card spending has higher impact on target variable and so must be included in the modeling\n",
    "- Number of customers who applied for Personal Loan are almost same whether the customers use the CreditCard issued by the bank or not\n",
    "- CreditCard doesn't seem to have much impact on the target variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Securities Account:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf93b1d0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=customers, x='Securities Account', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations:$\n",
    "- More number of customer who have Securities Account applied for Personal Loan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Online:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddf9a3400>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=customers, x='Online', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations:$\n",
    "- The number of customers who use internet banking and applied for Personal Loan are slighly higher than the customers who don't user internet banking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### CD Account:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddfa0a2b0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=customers, x='CD Account', hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations:$\n",
    "- The number of customers having CD Account is significantly less than those who don't have CD Account\n",
    "- The number of customers who have CD Account and applied for Personal Loan are less than the customers who don't have CD Account"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get the target column distribution. Your comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12ddfa75710>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "customers['Personal Loan'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4520\n",
       "1     480\n",
       "Name: Personal Loan, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers['Personal Loan'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Observations:$\n",
    "- Personal Loan is Categorical and Binary variable\n",
    "- Personal Loan is highly right-skewed distribution. Only 480 out of 4520 applied for the Personal Loan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. Delete Unwanted attribute:\n",
    "- ID is nominal variable and it won't have impact on the target variable of Personal Loan.\n",
    "- ZIP is a nominal variable. Ideally, it could have been processed if we know the geographical location of ZIP area OR it could have been processed with OneHotEncoding. Deleting ZIP in the current modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "customers.drop(labels=['ID', 'ZIP Code'], inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. Delete Attribute with low correlation (< 0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age                  -0.007726\n",
       "Experience           -0.007858\n",
       "Income                0.502462\n",
       "Family                0.061367\n",
       "CCAvg                 0.366889\n",
       "Education             0.136722\n",
       "Mortgage              0.142095\n",
       "Personal Loan         1.000000\n",
       "Securities Account    0.021954\n",
       "CD Account            0.316355\n",
       "Online                0.006278\n",
       "CreditCard            0.002802\n",
       "Name: Personal Loan, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.corr()['Personal Loan']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Deleting these features having less than 0.01 Correlation:\n",
    "- Age\n",
    "- Experience\n",
    "- Online\n",
    "- CreditCard"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is also evident from the Exploratory Data Analysis conducted above on which variables are impacting and which are not impacting the target variable of Personal Loan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "customers.drop(labels=['Age', 'Experience', 'Online', 'CreditCard'], inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Income                0.502462\n",
       "Family                0.061367\n",
       "CCAvg                 0.366889\n",
       "Education             0.136722\n",
       "Mortgage              0.142095\n",
       "Personal Loan         1.000000\n",
       "Securities Account    0.021954\n",
       "CD Account            0.316355\n",
       "Name: Personal Loan, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customers.corr()['Personal Loan']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x12ddfaefda0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1518x1440 with 72 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(customers, hue='Personal Loan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split the data into training and test set in the ratio of 70:30 respectively"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = customers['Personal Loan']\n",
    "X = customers.drop('Personal Loan', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of train records 3500\n",
      "Number of test records 1500\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=1)\n",
    "print('Number of train records', len(X_train))\n",
    "print('Number of test records', len(X_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use different classification models (Logistic, K-NN and Naïve Bayes) to predict the likelihood of a liability customer buying personal loans (15 points)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scale the features before creating models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc = StandardScaler()\n",
    "\n",
    "sc.fit(X_train)\n",
    "\n",
    "scaledX_train = sc.transform(X_train)\n",
    "scaledX_test = sc.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Logistic Regression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n",
       "                   multi_class='warn', n_jobs=None, penalty='l2',\n",
       "                   random_state=None, solver='warn', tol=0.0001, verbose=0,\n",
       "                   warm_start=False)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr_model = LogisticRegression()\n",
    "lr_model.fit(scaledX_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy:  0.9482857142857143\n",
      "Testing Accuracy:  0.944\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy: ', lr_model.score(scaledX_train, y_train))\n",
    "print('Testing Accuracy: ', lr_model.score(scaledX_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr_predict = lr_model.predict(scaledX_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### K-NN Model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "neighbours = list(range(1,31))\n",
    "knn_scores = list()\n",
    "for k in neighbours:\n",
    "    knn = KNeighborsClassifier(n_neighbors=k)\n",
    "    scores = cross_val_score(knn, scaledX_train, y_train, cv=10, scoring='accuracy')\n",
    "    knn_score = []\n",
    "    knn_score.append(k)\n",
    "    knn_score.append(scores.mean())\n",
    "    knn_scores.append(knn_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn_scores = pd.DataFrame(knn_scores, columns=['k', 'score'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Getting k value with maximum accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn_scores.sort_values(by=['score'], ascending=False, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>k</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.978289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>0.974005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>0.970005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   k     score\n",
       "0  1  0.978289\n",
       "1  3  0.974005\n",
       "2  5  0.970005"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_scores.reset_index(drop=True, inplace=True)\n",
    "knn_scores.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping the default value of 1 neighbour and getting next value\n",
      "\n",
      "Optimal neightbour value with maximum Accuracy:  3 \n",
      "Building the model again to get the prediction.\n"
     ]
    }
   ],
   "source": [
    "opt = knn_scores.loc[0, 'k']\n",
    "if opt == 1:\n",
    "    print('Skipping the default value of 1 neighbour and getting next value\\n')\n",
    "    opt = knn_scores.loc[1, 'k']\n",
    "print('Optimal neightbour value with maximum Accuracy: ', opt, '\\nBuilding the model again to get the prediction.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=3, p=2,\n",
       "                     weights='uniform')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn = KNeighborsClassifier(n_neighbors=opt)\n",
    "\n",
    "knn.fit(scaledX_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy :  0.9865714285714285\n",
      "Testing Accuracy:  0.9626666666666667\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy : ', knn.score(scaledX_train, y_train))\n",
    "print('Testing Accuracy: ', knn.score(scaledX_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn_predict = knn.predict(scaledX_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Naive Bayes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are three popular types of NaiveBayes model: Gaussian, MultiVariate and MultiBinomial.\n",
    "- Gaussian is used for Continuous data\n",
    "- MultiVariate is used for Descrete data\n",
    "- MultiBinomial is used for Binary data i.e. Text classification where many 0 and 1 present.\n",
    "\n",
    "In this problem, since most of the selected features are of Continuous type, we will use Gaussian model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GaussianNB(priors=None, var_smoothing=1e-09)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gaussian = GaussianNB()\n",
    "gaussian.fit(scaledX_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy:  0.8897142857142857\n",
      "Testing Accuracy:  0.8753333333333333\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy: ', gaussian.score(scaledX_train, y_train))\n",
    "print('Testing Accuracy: ', gaussian.score(scaledX_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "nb_predict = gaussian.predict(scaledX_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DecisionTree:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "depths = list(range(1,11))\n",
    "dt_scores = list()\n",
    "for depth in depths:\n",
    "    dt_model = DecisionTreeClassifier(criterion = 'entropy', max_depth=depth)\n",
    "    scores = cross_val_score(dt_model, scaledX_train, y_train, cv=10, scoring='accuracy')\n",
    "    dt_score = []\n",
    "    dt_score.append(depth)\n",
    "    dt_score.append(scores.mean())\n",
    "    dt_scores.append(dt_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt_scores = pd.DataFrame(dt_scores, columns=['depth', 'score'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "depth    4.000000\n",
       "score    0.987431\n",
       "Name: 3, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt = dt_scores.loc[dt_scores['score'].idxmax()]\n",
    "opt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimal depth value with maximum Accuracy:  4.0 \n",
      "Building the model again to get the prediction.\n"
     ]
    }
   ],
   "source": [
    "print('Optimal depth value with maximum Accuracy: ', opt.depth, '\\nBuilding the model again to get the prediction.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=4,\n",
       "                       max_features=None, max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, presort=False,\n",
       "                       random_state=None, splitter='best')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt_model = DecisionTreeClassifier(criterion = 'entropy', max_depth=opt.depth.astype(int))\n",
    "dt_model.fit(scaledX_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy:  0.9888571428571429\n",
      "Testing Accuracy:  0.9806666666666667\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy: ', dt_model.score(scaledX_train, y_train))\n",
    "print('Testing Accuracy: ', dt_model.score(scaledX_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt_predict = dt_model.predict(scaledX_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Print the confusion matrix for all the above models (5 points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1335,   16],\n",
       "       [  68,   81]], dtype=int64)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, lr_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear Regression Classification Report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.95      0.99      0.97      1351\n",
      "           1       0.84      0.54      0.66       149\n",
      "\n",
      "    accuracy                           0.94      1500\n",
      "   macro avg       0.89      0.77      0.81      1500\n",
      "weighted avg       0.94      0.94      0.94      1500\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Linear Regression Classification Report')\n",
    "print(classification_report(y_test, lr_predict))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1345,    6],\n",
       "       [  50,   99]], dtype=int64)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, knn_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KNN Model Classification Report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.96      1.00      0.98      1351\n",
      "           1       0.94      0.66      0.78       149\n",
      "\n",
      "    accuracy                           0.96      1500\n",
      "   macro avg       0.95      0.83      0.88      1500\n",
      "weighted avg       0.96      0.96      0.96      1500\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('KNN Model Classification Report')\n",
    "print(classification_report(y_test, knn_predict))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1228,  123],\n",
       "       [  64,   85]], dtype=int64)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, nb_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive Bayes Classification Report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.95      0.91      0.93      1351\n",
      "           1       0.41      0.57      0.48       149\n",
      "\n",
      "    accuracy                           0.88      1500\n",
      "   macro avg       0.68      0.74      0.70      1500\n",
      "weighted avg       0.90      0.88      0.88      1500\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Naive Bayes Classification Report')\n",
    "print(classification_report(y_test, nb_predict))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1344,    7],\n",
       "       [  22,  127]], dtype=int64)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, dt_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Classification Report\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      0.99      0.99      1351\n",
      "           1       0.95      0.85      0.90       149\n",
      "\n",
      "    accuracy                           0.98      1500\n",
      "   macro avg       0.97      0.92      0.94      1500\n",
      "weighted avg       0.98      0.98      0.98      1500\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Decision Tree Classification Report')\n",
    "print(classification_report(y_test, dt_predict))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Give your reasoning on which is the best model in this case and why it performs better? (5 points)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Summary of all of the models:\n",
    "- Decision Tree:\n",
    "    - Accuracy: 0.98\n",
    "    - f1-score: 0.90\n",
    "- KNN Model:\n",
    "    - Accuracy: 0.96\n",
    "    - f1-score: 0.78\n",
    "- Linear Regression:\n",
    "    - Accuracy: 0.94\n",
    "    - f1-score: 0.66\n",
    "- Naive Bayes:\n",
    "    - Accuracy: 0.88\n",
    "    - f1-score: 0.48\n",
    " \n",
    "### The accuracy and f1-score of all models are in decreasing order: DecisionTree, KNN, Logistic Regression and then Naive Bayes\n",
    "### Based on the accuracy and f1-score of all the models, DecisionTree model will work best."
   ]
  }
 ],
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