PfDA Assignment 2.ipynb

{
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   "source": [
    "# Investigation of the Wisconsin Breast Cancer dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7db7335e",
   "metadata": {},
   "source": [
    "![Image1](https://www.uicc.org/sites/main/files/thumbnails/image/Breast-cancer-graph-top-cancer-per-country-new-cases-2020-female-web.png_0.png)"
   ]
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   "source": [
    "### Problem Statement:<br>\n",
    "This project will investigate the Wisconsin Breast Cancer dataset. With a focus on the following:<br>\n",
    "\n",
    "* Undertake an analysis/review of the dataset and present an overview and background.<br>\n",
    "* Provide a literature review on classifiers which have been applied to the dataset and compare their performance.<br>\n",
    "* Present a statistical analysis of the dataset.<br>\n",
    "* Using a range of machine learning algorithms, train a set of classifiers on the dataset (using SKLearn etc.) and present classification performance results. Detail your rationale for the parameter selections you made while training the classifiers.<br>\n",
    "* Compare, contrast and critique your results with reference to the literature.<br>\n",
    "* Discuss and investigate how the dataset could be extended – using data synthesis of new tumour datapoints.<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dedafa5",
   "metadata": {},
   "source": [
    "### Breast Cancer:\n",
    "\n",
    "Breast cancer is one of the most common types of cancer in women, it occurs in every country of the world and in women at any age after puberty but with increasing rates in later life. Breast cancer treatment can be highly effective, especially when the disease is identified early. This dataset is extremely important as it offers so much versatility in reseach and analysis which could significantly assist in the treatment of this disease.\n",
    "\n",
    "This assignment presents a statistical analysis of the dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11c3f821",
   "metadata": {},
   "source": [
    "### Background on the Dataset:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b041b2b5",
   "metadata": {},
   "source": [
    "Dataset Title: Wisconsin Breast Cancer Database (January 8, 1991)<br>\n",
    "Source: Dr. WIlliam H. Wolberg (physician), University of Wisconsin Hospitals, Madison, Wisconsin, USA<br>\n",
    "\n",
    "(Please note, full citation found in Readme file)\n",
    "\n",
    "Data Set Characteristics: Multivariate\n",
    "Number of Instances: 699\n",
    "Area: Life\n",
    "Attribute Characteristics: Integer\n",
    "Number of Attributes: 10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bec8cc05",
   "metadata": {},
   "source": [
    "### Attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbfe4865",
   "metadata": {},
   "source": [
    "Dataset (original Attiributes):\n",
    "\n",
    "1. Sample code number: id number\n",
    "2. Clump Thickness: 1 - 10\n",
    "3. Uniformity of Cell Size: 1 - 10\n",
    "4. Uniformity of Cell Shape: 1 - 10\n",
    "5. Marginal Adhesion: 1 - 10\n",
    "6. Single Epithelial Cell Size: 1 - 10\n",
    "7. Bare Nuclei: 1 - 10\n",
    "8. Bland Chromatin: 1 - 10\n",
    "9. Normal Nucleoli: 1 - 10\n",
    "10. Mitoses: 1 - 10\n",
    "11. Class: (2 for benign, 4 for malignant)\n",
    "\n",
    "Per Dataset documentation;\n",
    "\n",
    "Missing attribute values: 16\n",
    "\n",
    "There are 16 instances in Groups 1 to 6 that contain a single missing \n",
    "(i.e., unavailable) attribute value, now denoted by \"?\"."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae15f19a",
   "metadata": {},
   "source": [
    "What is breast cancer?\n",
    "\n",
    "Breast cancer is when cells in your breast change and grow in an abnormal way. A group of these cancer cells can form a tumour."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "838c4e7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 1: Import dataset and required libraries:\n",
    "\n",
    "# NumPy for numerical operations\n",
    "import numpy as np\n",
    "\n",
    "# Pandas for data analysis\n",
    "import pandas as pd\n",
    "\n",
    "# pandas plotting\n",
    "from pandas.plotting import scatter_matrix\n",
    "\n",
    "# seaborn\n",
    "import seaborn as sns\n",
    "\n",
    "# random\n",
    "import random\n",
    "\n",
    "from scipy.stats import norm\n",
    "\n",
    "# Statistics for descriptive statistics\n",
    "import statistics\n",
    "\n",
    "# Matplotlib.pyplot for plotting\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Other plotting\n",
    "from scipy.stats import spearmanr\n",
    "from scipy.cluster import hierarchy\n",
    "from scipy.spatial.distance import squareform\n",
    "\n",
    "# sklearn\n",
    "import sklearn.neighbors as nei\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import classification_report, accuracy_score\n",
    "from sklearn.model_selection import  cross_val_score\n",
    "from sklearn import preprocessing\n",
    "from sklearn.datasets import load_breast_cancer\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.inspection import permutation_importance\n",
    "\n",
    "import pickle\n",
    "\n",
    "from collections import defaultdict\n",
    "\n",
    "# importing the dataset:\n",
    "\n",
    "# Creating file path variable:\n",
    "file_path = \"..\\PfDA_2\\wbc.data\"\n",
    "\n",
    "# above .data file is comma delimited \n",
    "wbc_data = pd.read_csv(file_path, delimiter=\",\")\n",
    "\n",
    "# Define columns in wbc_data\n",
    "wbc_data.columns = [\"Sample ID Number\", \"Clump Thickness\", \"Uniformity of Cell Size\", \"Uniformity of Cell Shape\", \"Marginal Adhesion\", \"Single Epithelial Cell Size\", \"Bare Nuclei\", \"Bland Chromatin\", \"Normal Nucleoli\", \"Mitosis\", \"Class\"]"
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   "cell_type": "code",
   "execution_count": 3,
   "id": "1374f81e",
   "metadata": {
    "scrolled": true
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       "      <th>Sample ID Number</th>\n",
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       "      <th>Normal Nucleoli</th>\n",
       "      <th>Mitosis</th>\n",
       "      <th>Class</th>\n",
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       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <th>4</th>\n",
       "      <td>1017122</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
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       "      <td>4</td>\n",
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      "text/plain": [
       "   Sample ID Number  Clump Thickness  Uniformity of Cell Size  \\\n",
       "0           1002945                5                        4   \n",
       "1           1015425                3                        1   \n",
       "2           1016277                6                        8   \n",
       "3           1017023                4                        1   \n",
       "4           1017122                8                       10   \n",
       "\n",
       "   Uniformity of Cell Shape  Marginal Adhesion  Single Epithelial Cell Size  \\\n",
       "0                         4                  5                            7   \n",
       "1                         1                  1                            2   \n",
       "2                         8                  1                            3   \n",
       "3                         1                  3                            2   \n",
       "4                        10                  8                            7   \n",
       "\n",
       "  Bare Nuclei  Bland Chromatin  Normal Nucleoli  Mitosis  Class  \n",
       "0          10                3                2        1      2  \n",
       "1           2                3                1        1      2  \n",
       "2           4                3                7        1      2  \n",
       "3           1                3                1        1      2  \n",
       "4          10                9                7        1      4  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # read the top/head of the dataset\n",
    "\n",
    "wbc_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6c5b9e66",
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       "      <th>Sample ID Number</th>\n",
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       "      <th>Uniformity of Cell Size</th>\n",
       "      <th>Uniformity of Cell Shape</th>\n",
       "      <th>Marginal Adhesion</th>\n",
       "      <th>Single Epithelial Cell Size</th>\n",
       "      <th>Bare Nuclei</th>\n",
       "      <th>Bland Chromatin</th>\n",
       "      <th>Normal Nucleoli</th>\n",
       "      <th>Mitosis</th>\n",
       "      <th>Class</th>\n",
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       "      <th>693</th>\n",
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       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>697</th>\n",
       "      <td>897471</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
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      "text/plain": [
       "     Sample ID Number  Clump Thickness  Uniformity of Cell Size  \\\n",
       "693            776715                3                        1   \n",
       "694            841769                2                        1   \n",
       "695            888820                5                       10   \n",
       "696            897471                4                        8   \n",
       "697            897471                4                        8   \n",
       "\n",
       "     Uniformity of Cell Shape  Marginal Adhesion  Single Epithelial Cell Size  \\\n",
       "693                         1                  1                            3   \n",
       "694                         1                  1                            2   \n",
       "695                        10                  3                            7   \n",
       "696                         6                  4                            3   \n",
       "697                         8                  5                            4   \n",
       "\n",
       "    Bare Nuclei  Bland Chromatin  Normal Nucleoli  Mitosis  Class  \n",
       "693           2                1                1        1      2  \n",
       "694           1                1                1        1      2  \n",
       "695           3                8               10        2      4  \n",
       "696           4               10                6        1      4  \n",
       "697           5               10                4        1      4  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read the foot/tail of the dataset\n",
    "\n",
    "wbc_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "22a22e09",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sample ID Number</th>\n",
       "      <th>Clump Thickness</th>\n",
       "      <th>Uniformity of Cell Size</th>\n",
       "      <th>Uniformity of Cell Shape</th>\n",
       "      <th>Marginal Adhesion</th>\n",
       "      <th>Single Epithelial Cell Size</th>\n",
       "      <th>Bland Chromatin</th>\n",
       "      <th>Normal Nucleoli</th>\n",
       "      <th>Mitosis</th>\n",
       "      <th>Class</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.980000e+02</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "      <td>698.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.071807e+06</td>\n",
       "      <td>4.416905</td>\n",
       "      <td>3.137536</td>\n",
       "      <td>3.210602</td>\n",
       "      <td>2.809456</td>\n",
       "      <td>3.217765</td>\n",
       "      <td>3.438395</td>\n",
       "      <td>2.869628</td>\n",
       "      <td>1.590258</td>\n",
       "      <td>2.690544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.175323e+05</td>\n",
       "      <td>2.817673</td>\n",
       "      <td>3.052575</td>\n",
       "      <td>2.972867</td>\n",
       "      <td>2.856606</td>\n",
       "      <td>2.215408</td>\n",
       "      <td>2.440056</td>\n",
       "      <td>3.055004</td>\n",
       "      <td>1.716162</td>\n",
       "      <td>0.951596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6.163400e+04</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>8.702582e+05</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.171710e+06</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.238354e+06</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.345435e+07</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Sample ID Number  Clump Thickness  Uniformity of Cell Size  \\\n",
       "count      6.980000e+02       698.000000               698.000000   \n",
       "mean       1.071807e+06         4.416905                 3.137536   \n",
       "std        6.175323e+05         2.817673                 3.052575   \n",
       "min        6.163400e+04         1.000000                 1.000000   \n",
       "25%        8.702582e+05         2.000000                 1.000000   \n",
       "50%        1.171710e+06         4.000000                 1.000000   \n",
       "75%        1.238354e+06         6.000000                 5.000000   \n",
       "max        1.345435e+07        10.000000                10.000000   \n",
       "\n",
       "       Uniformity of Cell Shape  Marginal Adhesion  \\\n",
       "count                698.000000         698.000000   \n",
       "mean                   3.210602           2.809456   \n",
       "std                    2.972867           2.856606   \n",
       "min                    1.000000           1.000000   \n",
       "25%                    1.000000           1.000000   \n",
       "50%                    1.000000           1.000000   \n",
       "75%                    5.000000           4.000000   \n",
       "max                   10.000000          10.000000   \n",
       "\n",
       "       Single Epithelial Cell Size  Bland Chromatin  Normal Nucleoli  \\\n",
       "count                   698.000000       698.000000       698.000000   \n",
       "mean                      3.217765         3.438395         2.869628   \n",
       "std                       2.215408         2.440056         3.055004   \n",
       "min                       1.000000         1.000000         1.000000   \n",
       "25%                       2.000000         2.000000         1.000000   \n",
       "50%                       2.000000         3.000000         1.000000   \n",
       "75%                       4.000000         5.000000         4.000000   \n",
       "max                      10.000000        10.000000        10.000000   \n",
       "\n",
       "          Mitosis       Class  \n",
       "count  698.000000  698.000000  \n",
       "mean     1.590258    2.690544  \n",
       "std      1.716162    0.951596  \n",
       "min      1.000000    2.000000  \n",
       "25%      1.000000    2.000000  \n",
       "50%      1.000000    2.000000  \n",
       "75%      1.000000    4.000000  \n",
       "max     10.000000    4.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Statistical analysis of the dataset using describe()\n",
    "\n",
    "wbc_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7829668f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sample ID Number               0\n",
       "Clump Thickness                0\n",
       "Uniformity of Cell Size        0\n",
       "Uniformity of Cell Shape       0\n",
       "Marginal Adhesion              0\n",
       "Single Epithelial Cell Size    0\n",
       "Bare Nuclei                    0\n",
       "Bland Chromatin                0\n",
       "Normal Nucleoli                0\n",
       "Mitosis                        0\n",
       "Class                          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Must check for any null values\n",
    "\n",
    "wbc_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "46854531",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample ID Number                int64\n",
      "Clump Thickness                 int64\n",
      "Uniformity of Cell Size         int64\n",
      "Uniformity of Cell Shape        int64\n",
      "Marginal Adhesion               int64\n",
      "Single Epithelial Cell Size     int64\n",
      "Bare Nuclei                    object\n",
      "Bland Chromatin                 int64\n",
      "Normal Nucleoli                 int64\n",
      "Mitosis                         int64\n",
      "Class                           int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "# Check the datatypes:\n",
    "\n",
    "print(wbc_data.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7048be1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(698, 11)\n"
     ]
    }
   ],
   "source": [
    "# Check shape of dataset\n",
    "\n",
    "print (wbc_data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "27a690b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sample ID number is not relevant to this analysis therefore it was identified to be removed.\n",
    "\n",
    "dummy_field = [\"Sample ID Number\"]\n",
    "\n",
    "wbc_data = wbc_data.drop(dummy_field, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bfb8dd1e",
   "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>Clump Thickness</th>\n",
       "      <th>Uniformity of Cell Size</th>\n",
       "      <th>Uniformity of Cell Shape</th>\n",
       "      <th>Marginal Adhesion</th>\n",
       "      <th>Single Epithelial Cell Size</th>\n",
       "      <th>Bare Nuclei</th>\n",
       "      <th>Bland Chromatin</th>\n",
       "      <th>Normal Nucleoli</th>\n",
       "      <th>Mitosis</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Clump Thickness  Uniformity of Cell Size  Uniformity of Cell Shape  \\\n",
       "0                5                        4                         4   \n",
       "1                3                        1                         1   \n",
       "2                6                        8                         8   \n",
       "3                4                        1                         1   \n",
       "4                8                       10                        10   \n",
       "\n",
       "   Marginal Adhesion  Single Epithelial Cell Size Bare Nuclei  \\\n",
       "0                  5                            7          10   \n",
       "1                  1                            2           2   \n",
       "2                  1                            3           4   \n",
       "3                  3                            2           1   \n",
       "4                  8                            7          10   \n",
       "\n",
       "   Bland Chromatin  Normal Nucleoli  Mitosis  Class  \n",
       "0                3                2        1      2  \n",
       "1                3                1        1      2  \n",
       "2                3                7        1      2  \n",
       "3                3                1        1      2  \n",
       "4                9                7        1      4  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking dataset to ensure \"Sample ID Number\" has been dropped\n",
    "\n",
    "wbc_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "399d3fe7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[RangeIndex(start=0, stop=698, step=1), Index(['Sample ID Number', 'Clump Thickness', 'Uniformity of Cell Size',\n",
      "       'Uniformity of Cell Shape', 'Marginal Adhesion',\n",
      "       'Single Epithelial Cell Size', 'Bare Nuclei', 'Bland Chromatin',\n",
      "       'Normal Nucleoli', 'Mitosis', 'Class'],\n",
      "      dtype='object')]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(698, 11)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wbc_data.replace('?',-99999, inplace = True)\n",
    "print(wbc_data.axes)\n",
    "wbc_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "75310005",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting some histograms focusing on Mitosis.\n",
    "\n",
    "wbc_data.hist(sharex=False, sharey=False, xlabelsize=1, ylabelsize=1)\n",
    "\n",
    "# plt.show()\n",
    "\n",
    "data_df = list(wbc_data.columns[0:10])\n",
    "\n",
    "X = wbc_data.loc[:, data_df]\n",
    "y = wbc_data[\"Mitosis\"]\n",
    "\n",
    "# Test options and evaluation metric\n",
    "num_folds = 10\n",
    "seed = 7\n",
    "scoring = 'accuracy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b6837a57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histograms\n",
    "\n",
    "wbc_data.hist(figsize=[10,10])\n",
    "plt.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "cc96f6d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1296 with 81 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_matrix(wbc_data,figsize=(18,18))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61aa98ca",
   "metadata": {},
   "source": [
    "Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f8af515d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Need to review the data types again in order to allow for modeling and make any adjustments:\n",
    "\n",
    "wbc_data.dtypes\n",
    "wbc_data[\"Bare Nuclei\"]=pd.to_numeric(wbc_data[\"Bare Nuclei\"],downcast='integer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "bc4fbb32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sample ID Number               int64\n",
       "Clump Thickness                int64\n",
       "Uniformity of Cell Size        int64\n",
       "Uniformity of Cell Shape       int64\n",
       "Marginal Adhesion              int64\n",
       "Single Epithelial Cell Size    int64\n",
       "Bare Nuclei                    int32\n",
       "Bland Chromatin                int64\n",
       "Normal Nucleoli                int64\n",
       "Mitosis                        int64\n",
       "Class                          int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reviewing the data types\n",
    "\n",
    "wbc_data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "398332fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping \"Class\" as it is not required for this model\n",
    "\n",
    "X= wbc_data.drop([\"Class\"],axis=1)\n",
    "y= wbc_data[\"Class\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0781818",
   "metadata": {},
   "source": [
    "### Train-Test Split\n",
    "\n",
    "Split arrays or matrices into random train and test subsets.\n",
    "\n",
    "Quick utility that wraps input validation, next(ShuffleSplit().split(X, y)), and application to input data into a single call for splitting (and optionally subsampling) data into a one-liner.\n",
    "\n",
    "https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "472c3dbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size= 0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d0fc82a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "seed=8\n",
    "scoring = 'accuracy'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0b78680",
   "metadata": {},
   "source": [
    "Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "eefe24a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('KNN', KNeighborsClassifier()), ('SVM', SVC())]\n"
     ]
    }
   ],
   "source": [
    "models=[]\n",
    "models.append(('KNN',KNeighborsClassifier(n_neighbors=5)))\n",
    "models.append(('SVM',SVC()))    \n",
    "print(models)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4d5ab0b",
   "metadata": {},
   "source": [
    "### Nearest Neighbors\n",
    "\n",
    "sklearn.neighbors provides functionality for unsupervised and supervised neighbors-based learning methods. Unsupervised nearest neighbors is the foundation of many other learning methods, notably manifold learning and spectral clustering. Supervised neighbors-based learning comes in two flavors: classification for data with discrete labels, and regression for data with continuous labels.\n",
    "\n",
    "https://scikit-learn.org/stable/modules/neighbors.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "f0a38397",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Using Sklearn nearest neighbors:\n",
    "\n",
    "model1=KNeighborsClassifier(n_neighbors=5)\n",
    "model1.fit(X_train, y_train)\n",
    "pickle.dump(model1, open('model1.pkl','wb'))\n",
    "\n",
    "#model1 = pickle.load(open('model1.pkl','rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f95108fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           2       0.66      0.76      0.71        89\n",
      "           4       0.43      0.31      0.36        51\n",
      "\n",
      "    accuracy                           0.60       140\n",
      "   macro avg       0.55      0.54      0.54       140\n",
      "weighted avg       0.58      0.60      0.58       140\n",
      "\n"
     ]
    }
   ],
   "source": [
    "predictions=model1.predict(X_test)\n",
    "print(accuracy_score(y_test,predictions))\n",
    "print(classification_report(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "eaaa200f",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "query data dimension must match training data dimension",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_17468/3645551866.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mmodel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'model1.pkl'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'rb'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0moutput\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\sklearn\\neighbors\\_classification.py\u001b[0m in \u001b[0;36mpredict\u001b[1;34m(self, X)\u001b[0m\n\u001b[0;32m    195\u001b[0m         \u001b[0mX\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'csr'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    196\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 197\u001b[1;33m         \u001b[0mneigh_dist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mneigh_ind\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkneighbors\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    198\u001b[0m         \u001b[0mclasses_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclasses_\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    199\u001b[0m         \u001b[0m_y\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_y\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\sklearn\\neighbors\\_base.py\u001b[0m in \u001b[0;36mkneighbors\u001b[1;34m(self, X, n_neighbors, return_distance)\u001b[0m\n\u001b[0;32m    720\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    721\u001b[0m                 \u001b[0mparallel_kwargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;34m\"prefer\"\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;34m\"threads\"\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 722\u001b[1;33m             chunked_results = Parallel(n_jobs, **parallel_kwargs)(\n\u001b[0m\u001b[0;32m    723\u001b[0m                 delayed(_tree_query_parallel_helper)(\n\u001b[0;32m    724\u001b[0m                     self._tree, X[s], n_neighbors, return_distance)\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, iterable)\u001b[0m\n\u001b[0;32m   1041\u001b[0m             \u001b[1;31m# remaining jobs.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1042\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1043\u001b[1;33m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdispatch_one_batch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1044\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_original_iterator\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1045\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\parallel.py\u001b[0m in \u001b[0;36mdispatch_one_batch\u001b[1;34m(self, iterator)\u001b[0m\n\u001b[0;32m    859\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    860\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 861\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_dispatch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtasks\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    862\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    863\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\parallel.py\u001b[0m in \u001b[0;36m_dispatch\u001b[1;34m(self, batch)\u001b[0m\n\u001b[0;32m    777\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    778\u001b[0m             \u001b[0mjob_idx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_jobs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 779\u001b[1;33m             \u001b[0mjob\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_async\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    780\u001b[0m             \u001b[1;31m# A job can complete so quickly than its callback is\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    781\u001b[0m             \u001b[1;31m# called before we get here, causing self._jobs to\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\_parallel_backends.py\u001b[0m in \u001b[0;36mapply_async\u001b[1;34m(self, func, callback)\u001b[0m\n\u001b[0;32m    206\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mapply_async\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    207\u001b[0m         \u001b[1;34m\"\"\"Schedule a func to be run\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 208\u001b[1;33m         \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mImmediateResult\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    209\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcallback\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    210\u001b[0m             \u001b[0mcallback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\_parallel_backends.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, batch)\u001b[0m\n\u001b[0;32m    570\u001b[0m         \u001b[1;31m# Don't delay the application, to avoid keeping the input\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    571\u001b[0m         \u001b[1;31m# arguments in memory\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 572\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbatch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    573\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    574\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    260\u001b[0m         \u001b[1;31m# change the default number of processes to -1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    261\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mparallel_backend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mn_jobs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_n_jobs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 262\u001b[1;33m             return [func(*args, **kwargs)\n\u001b[0m\u001b[0;32m    263\u001b[0m                     for func, args, kwargs in self.items]\n\u001b[0;32m    264\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\joblib\\parallel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    260\u001b[0m         \u001b[1;31m# change the default number of processes to -1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    261\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mparallel_backend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mn_jobs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_n_jobs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 262\u001b[1;33m             return [func(*args, **kwargs)\n\u001b[0m\u001b[0;32m    263\u001b[0m                     for func, args, kwargs in self.items]\n\u001b[0;32m    264\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\sklearn\\utils\\fixes.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m    220\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    221\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mconfig_context\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 222\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\sklearn\\neighbors\\_base.py\u001b[0m in \u001b[0;36m_tree_query_parallel_helper\u001b[1;34m(tree, *args, **kwargs)\u001b[0m\n\u001b[0;32m    545\u001b[0m     \u001b[0munder\u001b[0m \u001b[0mPyPy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    546\u001b[0m     \"\"\"\n\u001b[1;32m--> 547\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mtree\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    548\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    549\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32msklearn\\neighbors\\_binary_tree.pxi\u001b[0m in \u001b[0;36msklearn.neighbors._kd_tree.BinaryTree.query\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: query data dimension must match training data dimension"
     ]
    }
   ],
   "source": [
    "model = pickle.load(open('model1.pkl','rb'))\n",
    "output = model.predict([[4, 1, 1, 3, 2, 1, 3, 1, 1]])\n",
    "print(output[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ace6b35d",
   "metadata": {},
   "source": [
    "### Random Forest Classifier:\n",
    "\n",
    "A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is controlled with the max_samples parameter if bootstrap=True (default), otherwise the whole dataset is used to build each tree.\n",
    "\n",
    "https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "616432ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on test data: 0.97\n"
     ]
    }
   ],
   "source": [
    "# Random Forest Classsifier\n",
    "\n",
    "data = load_breast_cancer()\n",
    "X, y = data.data, data.target\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)\n",
    "\n",
    "clf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
    "clf.fit(X_train, y_train)\n",
    "print(\"Accuracy on test data: {:.2f}\".format(clf.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2e32b52a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "result = permutation_importance(clf, X_train, y_train, n_repeats=10, random_state=42)\n",
    "perm_sorted_idx = result.importances_mean.argsort()\n",
    "\n",
    "tree_importance_sorted_idx = np.argsort(clf.feature_importances_)\n",
    "tree_indices = np.arange(0, len(clf.feature_importances_)) + 0.5\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 8))\n",
    "ax1.barh(tree_indices, clf.feature_importances_[tree_importance_sorted_idx], height=0.7)\n",
    "ax1.set_yticks(tree_indices)\n",
    "ax1.set_yticklabels(data.feature_names[tree_importance_sorted_idx])\n",
    "ax1.set_ylim((0, len(clf.feature_importances_)))\n",
    "ax2.boxplot(\n",
    "    result.importances[perm_sorted_idx].T,\n",
    "    vert=False,\n",
    "    labels=data.feature_names[perm_sorted_idx],\n",
    ")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad01b33b",
   "metadata": {},
   "source": [
    "### Literatute Review:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ac47b0f",
   "metadata": {},
   "source": [
    "As noted by Lavanya, D in 'Analysis of Feature Selection with Classification: Breast Cancer Datasets'; \"Feature Selection increases the accuracy of the Classifier because it eliminates irrelevant attributes\", Classifiers can play a major part in understanding a dataset. With the use of machine learning classifiers can be trained in order for researchers to conduct essential studies and research.\n",
    "\n",
    "Additionally, Siham, M et al in 'Analysis of Breast Cancer Detection Using Different Machine Learning Techniques'; \"In order to minimize the bias associated with the random sampling of the training data, we use 10 fold cross validation after the pre-processing phase. In k-fold cross-validation, the original dataset is randomly partitioned into k equal size subsets.\" Attention to detail must be paid attention to with the random sampling of the training data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c5c9e50",
   "metadata": {},
   "source": [
    "### Conclusion:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0e8e6f9",
   "metadata": {},
   "source": [
    "As noted in the literature review by Lavanya, D. \"Classifiers can play a major part in understanding a dataset\", this assignment has given great insight into the abilities of machine learning and what can be gained by simulating datasets.\n",
    "\n",
    "This project analysed the dataset and then conducted some simulations in order to analyse the simulated results using machine learning and classifiers to classify samples."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d8b7843",
   "metadata": {},
   "source": [
    "### References:\n",
    "Can also be seen in [README.md](https://github.com/AndrewShanahan/PfDA_2/blob/main/README.md) file.\n",
    "\n",
    "#### Initial set-up - Troubleshooting repository set up:<br>\n",
    "[01] https://stackoverflow.com/questions/17096311/why-do-i-need-to-explicitly-push-a-new-branch/17096880#17096880<br>\n",
    "[02] https://www.educative.io/answers/the-fatal-refusing-to-merge-unrelated-histories-git-error<br>\n",
    "\n",
    "#### Readme:<br>\n",
    "[03] https://www.freecodecamp.org/news/how-to-write-a-good-readme-file/<br>\n",
    "\n",
    "#### Wisconsin Breast Cancer dataset:<br>\n",
    "[04] Dataset info/descriptoin https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Original%290<br>\n",
    "[05] https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+%28original%29<br>\n",
    "[06] https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic)<br>\n",
    "[07] https://data.world/health/breast-cancer-wisconsin<br>\n",
    "[08] Importing dataset and troubleshooting: https://stackoverflow.com/questions/31797013/how-to-open-a-data-file-extension<br>\n",
    "[09] Attribute Information: https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+%28original%29<br>\n",
    "[10] https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html<br>\n",
    "\n",
    "#### Breast Cancer:<br>\n",
    "[11] https://www2.hse.ie/conditions/breast-cancer-women/?gclid=CjwKCAiAnZCdBhBmEiwA8nDQxV9FZLIuR4GMAzCaJFwNTvHQGzP8oK-LCGZ-jOYXBTyNlzBNjKMK6RoCzLkQAvD_BwE&gclsrc=aw.ds<br>\n",
    "[12] https://www.cancer.ie/cancer-information-and-support/cancer-types/breast-cancer<br>\n",
    "[13] https://www.who.int/news-room/fact-sheets/detail/breast-cancer<br>\n",
    "\n",
    "#### Literature Review:<br>\n",
    "[14] Lavanya, D. (05/11/2011) ‘Analysis of feature selection with classification: Breast Cancer Datasets’, Indian Journal of Computer Science and Engineering, ISSN : 0976-5166, P. xxx. Available at: http://ijcse.com/docs/INDJCSE11-02-05-167.pdf (Accessed: 29/12/2022).<br>\n",
    "\n",
    "[15] Siham, M et al. (11/07/2020) 'Analysis of Breast Cancer Detection Using Different Machine Learning Techniques', Communications in Computer and Information Science, ISSN 1234, P. xxx. Available at: https://link.springer.com/chapter/10.1007/978-981-15-7205-0_10#Sec2 (Accessed: 01/01/2022).<br>\n",
    "\n",
    "#### Sklearn:<br>\n",
    "[16] https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html<br>\n",
    "[17] https://scikit-learn.org/stable/modules/neighbors.html<br>\n",
    "[18] https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html<br>\n",
    "\n",
    "#### Other Resources Used:<br>\n",
    "[19] Datacamp - numerous courses/tracks completed over last number of months have supported this exercise: https://www.datacamp.com/<br>\n",
    "[20] Udemy course: https://www.udemy.com/course/the-modern-python3-bootcamp/learn/lecture/8680110?start=94#overview<br>\n",
    "[21] W3schools - Resource used on regular basis: https://www.w3schools.com/<br>\n",
    "[22] Stackoverflow - Resource used to help troubleshoot problems and help with coding: https://stackoverflow.com/<br>\n",
    "[23] matplotlyb.plyplot:https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html<br>\n",
    "[24] pandas: https://pandas.pydata.org/<br>\n",
    "[25] numpy: https://numpy.org/doc/stable/index.html<br>"
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