training3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sklearn as sk\n",
    "import matplotlib.pyplot as plt\n",
    "import json\n",
    "import math\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.  Read Dataset and remove NAN values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat      cut color clarity  depth  table  price     x     y     z\n",
       "0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43\n",
       "1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31\n",
       "2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31\n",
       "3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63\n",
       "4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds = pd.read_csv('diamonds.csv')\n",
    "\n",
    "diamonds.dropna(inplace=True)\n",
    "diamonds.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.  Mapping non-numerical values to numerical ones"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Cut Quality**\n",
    "| Cut        | Mapping |\n",
    "|------------|------|\n",
    "| Ideal      | 0    |\n",
    "| Premium    | 1    |\n",
    "| Good       | 2    |\n",
    "| Very Good  | 3    |\n",
    "| Fair       | 4    |\n",
    "\n",
    "**Color Grade**\n",
    "| Color | Mapping |\n",
    "|-------|------|\n",
    "| E     | 0    |\n",
    "| I     | 1    |\n",
    "| J     | 2    |\n",
    "| H     | 3    |\n",
    "| F     | 4    |\n",
    "| G     | 5    |\n",
    "| D     | 6    |\n",
    "\n",
    "**Clarity Grade**\n",
    "| Clarity | Mapping |\n",
    "|---------|------|\n",
    "| SI2     | 0    |\n",
    "| SI1     | 1    |\n",
    "| VS1     | 2    |\n",
    "| VS2     | 3    |\n",
    "| VVS2    | 4    |\n",
    "| VVS1    | 5    |\n",
    "| I1      | 6    |\n",
    "| IF      | 7    |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cut_mapping = {cut: i for i, cut in enumerate(diamonds['cut'].unique())}\n",
    "color_mapping = {color: i for i, color in enumerate(diamonds['color'].unique())}\n",
    "clarity_mapping = {clarity: i for i, clarity in enumerate(diamonds['clarity'].unique())}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.  Replace the non-numerical columns with their numerical mappings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "diamonds_numerical = diamonds.copy()\n",
    "diamonds_numerical['cut'] = diamonds['cut'].map(cut_mapping)\n",
    "diamonds_numerical['color'] = diamonds['color'].map(color_mapping)\n",
    "diamonds_numerical['clarity'] = diamonds['clarity'].map(clarity_mapping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>price</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2207</th>\n",
       "      <td>1.00</td>\n",
       "      <td>Premium</td>\n",
       "      <td>G</td>\n",
       "      <td>SI2</td>\n",
       "      <td>59.1</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3142</td>\n",
       "      <td>6.55</td>\n",
       "      <td>6.48</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2314</th>\n",
       "      <td>1.01</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>I1</td>\n",
       "      <td>58.1</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3167</td>\n",
       "      <td>6.66</td>\n",
       "      <td>6.60</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4791</th>\n",
       "      <td>1.10</td>\n",
       "      <td>Premium</td>\n",
       "      <td>G</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3696</td>\n",
       "      <td>6.50</td>\n",
       "      <td>6.47</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5471</th>\n",
       "      <td>1.01</td>\n",
       "      <td>Premium</td>\n",
       "      <td>F</td>\n",
       "      <td>SI2</td>\n",
       "      <td>59.2</td>\n",
       "      <td>58.0</td>\n",
       "      <td>3837</td>\n",
       "      <td>6.50</td>\n",
       "      <td>6.47</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10167</th>\n",
       "      <td>1.50</td>\n",
       "      <td>Good</td>\n",
       "      <td>G</td>\n",
       "      <td>I1</td>\n",
       "      <td>64.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>4731</td>\n",
       "      <td>7.15</td>\n",
       "      <td>7.04</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11182</th>\n",
       "      <td>1.07</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>F</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.6</td>\n",
       "      <td>56.0</td>\n",
       "      <td>4954</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.62</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11963</th>\n",
       "      <td>1.00</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>H</td>\n",
       "      <td>VS2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>53.0</td>\n",
       "      <td>5139</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13601</th>\n",
       "      <td>1.15</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>VS2</td>\n",
       "      <td>59.2</td>\n",
       "      <td>56.0</td>\n",
       "      <td>5564</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.83</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15951</th>\n",
       "      <td>1.14</td>\n",
       "      <td>Fair</td>\n",
       "      <td>G</td>\n",
       "      <td>VS1</td>\n",
       "      <td>57.5</td>\n",
       "      <td>67.0</td>\n",
       "      <td>6381</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24394</th>\n",
       "      <td>2.18</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>SI2</td>\n",
       "      <td>59.4</td>\n",
       "      <td>61.0</td>\n",
       "      <td>12631</td>\n",
       "      <td>8.49</td>\n",
       "      <td>8.45</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24520</th>\n",
       "      <td>1.56</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>54.0</td>\n",
       "      <td>12800</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26123</th>\n",
       "      <td>2.25</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>SI1</td>\n",
       "      <td>61.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>15397</td>\n",
       "      <td>8.52</td>\n",
       "      <td>8.42</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26243</th>\n",
       "      <td>1.20</td>\n",
       "      <td>Premium</td>\n",
       "      <td>D</td>\n",
       "      <td>VVS1</td>\n",
       "      <td>62.1</td>\n",
       "      <td>59.0</td>\n",
       "      <td>15686</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27112</th>\n",
       "      <td>2.20</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>SI1</td>\n",
       "      <td>61.2</td>\n",
       "      <td>59.0</td>\n",
       "      <td>17265</td>\n",
       "      <td>8.42</td>\n",
       "      <td>8.37</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27429</th>\n",
       "      <td>2.25</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.8</td>\n",
       "      <td>59.0</td>\n",
       "      <td>18034</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27503</th>\n",
       "      <td>2.02</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.7</td>\n",
       "      <td>53.0</td>\n",
       "      <td>18207</td>\n",
       "      <td>8.02</td>\n",
       "      <td>7.95</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27739</th>\n",
       "      <td>2.80</td>\n",
       "      <td>Good</td>\n",
       "      <td>G</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.8</td>\n",
       "      <td>58.0</td>\n",
       "      <td>18788</td>\n",
       "      <td>8.90</td>\n",
       "      <td>8.85</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49556</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Good</td>\n",
       "      <td>F</td>\n",
       "      <td>SI2</td>\n",
       "      <td>64.1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2130</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49557</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Good</td>\n",
       "      <td>F</td>\n",
       "      <td>SI2</td>\n",
       "      <td>64.1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2130</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51506</th>\n",
       "      <td>1.12</td>\n",
       "      <td>Premium</td>\n",
       "      <td>G</td>\n",
       "      <td>I1</td>\n",
       "      <td>60.4</td>\n",
       "      <td>59.0</td>\n",
       "      <td>2383</td>\n",
       "      <td>6.71</td>\n",
       "      <td>6.67</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       carat        cut color clarity  depth  table  price     x     y    z\n",
       "2207    1.00    Premium     G     SI2   59.1   59.0   3142  6.55  6.48  0.0\n",
       "2314    1.01    Premium     H      I1   58.1   59.0   3167  6.66  6.60  0.0\n",
       "4791    1.10    Premium     G     SI2   63.0   59.0   3696  6.50  6.47  0.0\n",
       "5471    1.01    Premium     F     SI2   59.2   58.0   3837  6.50  6.47  0.0\n",
       "10167   1.50       Good     G      I1   64.0   61.0   4731  7.15  7.04  0.0\n",
       "11182   1.07      Ideal     F     SI2   61.6   56.0   4954  0.00  6.62  0.0\n",
       "11963   1.00  Very Good     H     VS2   63.3   53.0   5139  0.00  0.00  0.0\n",
       "13601   1.15      Ideal     G     VS2   59.2   56.0   5564  6.88  6.83  0.0\n",
       "15951   1.14       Fair     G     VS1   57.5   67.0   6381  0.00  0.00  0.0\n",
       "24394   2.18    Premium     H     SI2   59.4   61.0  12631  8.49  8.45  0.0\n",
       "24520   1.56      Ideal     G     VS2   62.2   54.0  12800  0.00  0.00  0.0\n",
       "26123   2.25    Premium     I     SI1   61.3   58.0  15397  8.52  8.42  0.0\n",
       "26243   1.20    Premium     D    VVS1   62.1   59.0  15686  0.00  0.00  0.0\n",
       "27112   2.20    Premium     H     SI1   61.2   59.0  17265  8.42  8.37  0.0\n",
       "27429   2.25    Premium     H     SI2   62.8   59.0  18034  0.00  0.00  0.0\n",
       "27503   2.02    Premium     H     VS2   62.7   53.0  18207  8.02  7.95  0.0\n",
       "27739   2.80       Good     G     SI2   63.8   58.0  18788  8.90  8.85  0.0\n",
       "49556   0.71       Good     F     SI2   64.1   60.0   2130  0.00  0.00  0.0\n",
       "49557   0.71       Good     F     SI2   64.1   60.0   2130  0.00  0.00  0.0\n",
       "51506   1.12    Premium     G      I1   60.4   59.0   2383  6.71  6.67  0.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# store rows where x or y or z is 0\n",
    "zero_rows = diamonds[(diamonds['x'] == 0) | (diamonds['y'] == 0) | (diamonds['z'] == 0)]\n",
    "zero_rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop rows with outliers (x = 0, y = 0 or z = 0)\n",
    "mask = (diamonds_numerical['x'] == 0) | (diamonds_numerical['y'] == 0) | (diamonds_numerical['z'] == 0)\n",
    "diamonds_numerical = diamonds_numerical.drop(diamonds_numerical[mask].index)\n",
    "# write diamonds_numerical to csv\n",
    "diamonds_numerical.to_csv('diamonds_numerical.csv', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1500 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating separate plots for each feature against price\n",
    "fig, axes = plt.subplots(nrows=3, ncols=3, figsize=(15, 15))\n",
    "fig.subplots_adjust(hspace=0.5, wspace=0.3)\n",
    "\n",
    "# List of all the features except price\n",
    "features = diamonds_numerical.columns.drop('price')\n",
    "\n",
    "# Plot each feature against price\n",
    "for ax, feature in zip(axes.flatten(), features):\n",
    "    ax.scatter(diamonds_numerical[feature], diamonds_numerical['price'], alpha=0.5)\n",
    "    ax.set_title(f'{feature} vs. Price')\n",
    "    ax.set_xlabel(feature)\n",
    "    ax.set_ylabel('Price')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>carat</th>\n",
       "      <th>cut</th>\n",
       "      <th>color</th>\n",
       "      <th>clarity</th>\n",
       "      <th>depth</th>\n",
       "      <th>table</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat  cut  color  clarity  depth  table     x     y     z\n",
       "0   0.23    0      0        0   61.5   55.0  3.95  3.98  2.43\n",
       "1   0.21    1      0        1   59.8   61.0  3.89  3.84  2.31\n",
       "2   0.23    2      0        2   56.9   65.0  4.05  4.07  2.31\n",
       "3   0.29    1      1        3   62.4   58.0  4.20  4.23  2.63\n",
       "4   0.31    2      2        0   63.3   58.0  4.34  4.35  2.75"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = diamonds_numerical.drop('price', axis = 1)\n",
    "y = diamonds_numerical['price']\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    326\n",
       "1    326\n",
       "2    327\n",
       "3    334\n",
       "4    335\n",
       "Name: price, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "model = LinearRegression()\n",
    "# Train the models\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 2029299.0804379764\n",
      "R^2 Score: 0.8723456077895886\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "print(\"Mean Squared Error:\", mse)\n",
    "print(\"R^2 Score:\", r2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=100, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=42, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=100, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=42, ...)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             multi_strategy=None, n_estimators=100, n_jobs=None,\n",
       "             num_parallel_tree=None, random_state=42, ...)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xgboost import XGBRegressor\n",
    "model2 = XGBRegressor(n_estimators=100,random_state=42)\n",
    "model2.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 314752.8223018785\n",
      "R^2 Score: 0.9802002668730396\n"
     ]
    }
   ],
   "source": [
    "y_pred2 = model2.predict(X_test)\n",
    "mse2 = mean_squared_error(y_test, y_pred2)\n",
    "r22 = r2_score(y_test, y_pred2)\n",
    "print(\"Mean Squared Error:\", mse2)\n",
    "print(\"R^2 Score:\", r22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fadi/Desktop/dev/sas2/ws-23-sas-02/sas2/lib/python3.10/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (500) reached and the optimization hasn't converged yet.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>MLPRegressor(max_iter=500, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MLPRegressor</label><div class=\"sk-toggleable__content\"><pre>MLPRegressor(max_iter=500, random_state=42)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "MLPRegressor(max_iter=500, random_state=42)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neural_network import MLPRegressor\n",
    "model4 = MLPRegressor(random_state=42, max_iter=500)\n",
    "model4.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 2029299.0804379764\n",
      "MSE 2  314752.8223018785\n",
      "MSE 4  1320105.4212450413\n",
      "R^2 Score: 0.8723456077895886\n",
      "R^2 Score: 0.9802002668730396\n",
      "R^2 Score: 0.9169579009682819\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "# Predict on the test set\n",
    "y_pred = model.predict(X_test)\n",
    "y_pred2 = model2.predict(X_test)\n",
    "y_pred4 = model4.predict(X_test)\n",
    "# Evaluate the model\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "mse2 = mean_squared_error(y_test, y_pred2)\n",
    "mse4 = mean_squared_error(y_test, y_pred4)\n",
    "r2 = r2_score(y_test, y_pred)\n",
    "r22 = r2_score(y_test, y_pred2)\n",
    "r24 = r2_score(y_test, y_pred4)\n",
    "print(\"Mean Squared Error:\", mse)\n",
    "print(\"MSE 2 \", mse2)\n",
    "print(\"MSE 4 \", mse4)\n",
    "print(\"R^2 Score:\", r2)\n",
    "print(\"R^2 Score:\", r22)\n",
    "print(\"R^2 Score:\", r24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3461.6711], dtype=float32)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_diamond = [[\n",
    "    1.00,\n",
    "    2,\n",
    "    1,\n",
    "    1,\n",
    "    60.4,\n",
    "    55,\n",
    "    4.20,\n",
    "    4.3,\n",
    "    2.27\n",
    "]]\n",
    "model2.predict(test_diamond)\n"
   ]
  },
  {
   "cell_type": "code",