Concrete Strength Assignment.ipynb

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    "# Assignment: Compresive Strength Concrete Problem\n",
    "\n",
    "\n",
    "### Abstract: \n",
    "\n",
    "Concrete is the most important material in civil engineering. The concrete compressive strength (concrete strength to bear the load) is a highly nonlinear function of age and ingredients.  <br><br>\n",
    "\n",
    "<table border=\"1\"  cellpadding=\"6\" bordercolor=\"red\">\n",
    "\t<tbody>\n",
    "        <tr>\n",
    "\t\t<td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Data Set Characteristics:&nbsp;&nbsp;</b></p></td>\n",
    "\t\t<td><p class=\"normal\">Multivariate</p></td>\n",
    "\t\t<td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Number of Instances:</b></p></td>\n",
    "\t\t<td><p class=\"normal\">1030</p></td>\n",
    "\t\t<td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Area:</b></p></td>\n",
    "\t\t<td><p class=\"normal\">Physical</p></td>\n",
    "        </tr>\n",
    "     </tbody>\n",
    "    </table>\n",
    "<table border=\"1\" cellpadding=\"6\">\n",
    "    <tbody>\n",
    "        <tr>\n",
    "            <td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Attribute Characteristics:</b></p></td>\n",
    "            <td><p class=\"normal\">Real</p></td>\n",
    "            <td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Number of Attributes:</b></p></td>\n",
    "            <td><p class=\"normal\">9</p></td>\n",
    "            <td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Date Donated</b></p></td>\n",
    "            <td><p class=\"normal\">2007-08-03</p></td>\n",
    "        </tr>\n",
    "     </tbody>\n",
    "    </table>\n",
    "<table border=\"1\" cellpadding=\"6\">\t\n",
    "    <tbody>\n",
    "    <tr>\n",
    "\t\t<td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Associated Tasks:</b></p></td>\n",
    "\t\t<td><p class=\"normal\">Regression</p></td>\n",
    "\t\t<td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Missing Values?</b></p></td>\n",
    "\t\t<td><p class=\"normal\">N/A</p></td>\n",
    "\t\t<td bgcolor=\"#DDEEFF\"><p class=\"normal\"><b>Number of Web Hits:</b></p></td>\n",
    "\t\t<td><p class=\"normal\">231464</p></td>\n",
    "\t</tr>\n",
    "    </tbody>\n",
    "    </table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Description:\n",
    "| Features Name | Data Type | Measurement | Description |\n",
    "| -- | -- | -- | -- |\n",
    "Cement (component 1) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Blast Furnace Slag (component 2) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Fly Ash (component 3) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Water (component 4) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Superplasticizer (component 5) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Coarse Aggregate (component 6) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Fine Aggregate (component 7) | quantitative | kg in a m3 mixture | Input Variable\n",
    "Age | quantitative | Day (1~365) | Input Variable\n",
    "Concrete compressive strength | quantitative | MPa | Output Variable\n",
    "\n",
    "### WORKFLOW :\n",
    "- Load Data\n",
    "- Check Missing Values ( If Exist ; Fill each record with mean of its feature )\n",
    "- Standardized the Input Variables. **Hint**: Centeralized the data\n",
    "- Split into 50% Training(Samples,Labels) , 30% Test(Samples,Labels) and 20% Validation Data(Samples,Labels).\n",
    "- Model : input Layer (No. of features ), 3 hidden layers including 10,8,6 unit & Output Layer with activation function relu/tanh (check by experiment).\n",
    "- Compilation Step (Note : Its a Regression problem , select loss , metrics according to it)\n",
    "- Train the Model with Epochs (100) and validate it\n",
    "- If the model gets overfit tune your model by changing the units , No. of layers , activation function , epochs , add dropout layer or add Regularizer according to the need .\n",
    "- Evaluation Step\n",
    "- Prediction\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Data:\n",
    "[Click Here to Download DataSet](https://github.com/ramsha275/ML_Datasets/blob/main/compresive_strength_concrete.csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tp\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cement (component 1)(kg in a m^3 mixture)</th>\n",
       "      <th>Blast Furnace Slag (component 2)(kg in a m^3 mixture)</th>\n",
       "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
       "      <th>Water  (component 4)(kg in a m^3 mixture)</th>\n",
       "      <th>Superplasticizer (component 5)(kg in a m^3 mixture)</th>\n",
       "      <th>Coarse Aggregate  (component 6)(kg in a m^3 mixture)</th>\n",
       "      <th>Fine Aggregate (component 7)(kg in a m^3 mixture)</th>\n",
       "      <th>Age (day)</th>\n",
       "      <th>Concrete compressive strength(MPa, megapascals)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>540.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>676.0</td>\n",
       "      <td>28</td>\n",
       "      <td>79.99</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>540.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1055.0</td>\n",
       "      <td>676.0</td>\n",
       "      <td>28</td>\n",
       "      <td>61.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>332.5</td>\n",
       "      <td>142.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>932.0</td>\n",
       "      <td>594.0</td>\n",
       "      <td>270</td>\n",
       "      <td>40.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>332.5</td>\n",
       "      <td>142.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>932.0</td>\n",
       "      <td>594.0</td>\n",
       "      <td>365</td>\n",
       "      <td>41.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>198.6</td>\n",
       "      <td>132.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>978.4</td>\n",
       "      <td>825.5</td>\n",
       "      <td>360</td>\n",
       "      <td>44.30</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1025</th>\n",
       "      <td>276.4</td>\n",
       "      <td>116.0</td>\n",
       "      <td>90.3</td>\n",
       "      <td>179.6</td>\n",
       "      <td>8.9</td>\n",
       "      <td>870.1</td>\n",
       "      <td>768.3</td>\n",
       "      <td>28</td>\n",
       "      <td>44.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1026</th>\n",
       "      <td>322.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.6</td>\n",
       "      <td>196.0</td>\n",
       "      <td>10.4</td>\n",
       "      <td>817.9</td>\n",
       "      <td>813.4</td>\n",
       "      <td>28</td>\n",
       "      <td>31.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1027</th>\n",
       "      <td>148.5</td>\n",
       "      <td>139.4</td>\n",
       "      <td>108.6</td>\n",
       "      <td>192.7</td>\n",
       "      <td>6.1</td>\n",
       "      <td>892.4</td>\n",
       "      <td>780.0</td>\n",
       "      <td>28</td>\n",
       "      <td>23.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1028</th>\n",
       "      <td>159.1</td>\n",
       "      <td>186.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>175.6</td>\n",
       "      <td>11.3</td>\n",
       "      <td>989.6</td>\n",
       "      <td>788.9</td>\n",
       "      <td>28</td>\n",
       "      <td>32.77</td>\n",
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       "    <tr>\n",
       "      <th>1029</th>\n",
       "      <td>260.9</td>\n",
       "      <td>100.5</td>\n",
       "      <td>78.3</td>\n",
       "      <td>200.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>864.5</td>\n",
       "      <td>761.5</td>\n",
       "      <td>28</td>\n",
       "      <td>32.40</td>\n",
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       "      Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "0                                         540.0   \n",
       "1                                         540.0   \n",
       "2                                         332.5   \n",
       "3                                         332.5   \n",
       "4                                         198.6   \n",
       "...                                         ...   \n",
       "1025                                      276.4   \n",
       "1026                                      322.2   \n",
       "1027                                      148.5   \n",
       "1028                                      159.1   \n",
       "1029                                      260.9   \n",
       "\n",
       "      Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "0                                                   0.0       \n",
       "1                                                   0.0       \n",
       "2                                                 142.5       \n",
       "3                                                 142.5       \n",
       "4                                                 132.4       \n",
       "...                                                 ...       \n",
       "1025                                              116.0       \n",
       "1026                                                0.0       \n",
       "1027                                              139.4       \n",
       "1028                                              186.7       \n",
       "1029                                              100.5       \n",
       "\n",
       "      Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "0                                            0.0   \n",
       "1                                            0.0   \n",
       "2                                            0.0   \n",
       "3                                            0.0   \n",
       "4                                            0.0   \n",
       "...                                          ...   \n",
       "1025                                        90.3   \n",
       "1026                                       115.6   \n",
       "1027                                       108.6   \n",
       "1028                                         0.0   \n",
       "1029                                        78.3   \n",
       "\n",
       "      Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "0                                         162.0   \n",
       "1                                         162.0   \n",
       "2                                         228.0   \n",
       "3                                         228.0   \n",
       "4                                         192.0   \n",
       "...                                         ...   \n",
       "1025                                      179.6   \n",
       "1026                                      196.0   \n",
       "1027                                      192.7   \n",
       "1028                                      175.6   \n",
       "1029                                      200.6   \n",
       "\n",
       "      Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "0                                                   2.5     \n",
       "1                                                   2.5     \n",
       "2                                                   0.0     \n",
       "3                                                   0.0     \n",
       "4                                                   0.0     \n",
       "...                                                 ...     \n",
       "1025                                                8.9     \n",
       "1026                                               10.4     \n",
       "1027                                                6.1     \n",
       "1028                                               11.3     \n",
       "1029                                                8.6     \n",
       "\n",
       "      Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "0                                                1040.0      \n",
       "1                                                1055.0      \n",
       "2                                                 932.0      \n",
       "3                                                 932.0      \n",
       "4                                                 978.4      \n",
       "...                                                 ...      \n",
       "1025                                              870.1      \n",
       "1026                                              817.9      \n",
       "1027                                              892.4      \n",
       "1028                                              989.6      \n",
       "1029                                              864.5      \n",
       "\n",
       "      Fine Aggregate (component 7)(kg in a m^3 mixture)  Age (day)  \\\n",
       "0                                                 676.0         28   \n",
       "1                                                 676.0         28   \n",
       "2                                                 594.0        270   \n",
       "3                                                 594.0        365   \n",
       "4                                                 825.5        360   \n",
       "...                                                 ...        ...   \n",
       "1025                                              768.3         28   \n",
       "1026                                              813.4         28   \n",
       "1027                                              780.0         28   \n",
       "1028                                              788.9         28   \n",
       "1029                                              761.5         28   \n",
       "\n",
       "      Concrete compressive strength(MPa, megapascals)   \n",
       "0                                                79.99  \n",
       "1                                                61.89  \n",
       "2                                                40.27  \n",
       "3                                                41.05  \n",
       "4                                                44.30  \n",
       "...                                                ...  \n",
       "1025                                             44.28  \n",
       "1026                                             31.18  \n",
       "1027                                             23.70  \n",
       "1028                                             32.77  \n",
       "1029                                             32.40  \n",
       "\n",
       "[1030 rows x 9 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('compresive_strength_concrete.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1030, 9)"
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     "execution_count": 34,
     "metadata": {},
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    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cement (component 1)(kg in a m^3 mixture)                0\n",
       "Blast Furnace Slag (component 2)(kg in a m^3 mixture)    0\n",
       "Fly Ash (component 3)(kg in a m^3 mixture)               0\n",
       "Water  (component 4)(kg in a m^3 mixture)                0\n",
       "Superplasticizer (component 5)(kg in a m^3 mixture)      0\n",
       "Coarse Aggregate  (component 6)(kg in a m^3 mixture)     0\n",
       "Fine Aggregate (component 7)(kg in a m^3 mixture)        0\n",
       "Age (day)                                                0\n",
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     "execution_count": 35,
     "metadata": {},
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   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cement (component 1)(kg in a m^3 mixture)                float64\n",
       "Blast Furnace Slag (component 2)(kg in a m^3 mixture)    float64\n",
       "Fly Ash (component 3)(kg in a m^3 mixture)               float64\n",
       "Water  (component 4)(kg in a m^3 mixture)                float64\n",
       "Superplasticizer (component 5)(kg in a m^3 mixture)      float64\n",
       "Coarse Aggregate  (component 6)(kg in a m^3 mixture)     float64\n",
       "Fine Aggregate (component 7)(kg in a m^3 mixture)        float64\n",
       "Age (day)                                                  int64\n",
       "Concrete compressive strength(MPa, megapascals)          float64\n",
       "dtype: object"
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     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
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       "      <td>228.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>594.0</td>\n",
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      ],
      "text/plain": [
       "   Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "0                                      540.0   \n",
       "1                                      540.0   \n",
       "2                                      332.5   \n",
       "3                                      332.5   \n",
       "4                                      198.6   \n",
       "\n",
       "   Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "0                                                0.0       \n",
       "1                                                0.0       \n",
       "2                                              142.5       \n",
       "3                                              142.5       \n",
       "4                                              132.4       \n",
       "\n",
       "   Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "0                                         0.0   \n",
       "1                                         0.0   \n",
       "2                                         0.0   \n",
       "3                                         0.0   \n",
       "4                                         0.0   \n",
       "\n",
       "   Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "0                                      162.0   \n",
       "1                                      162.0   \n",
       "2                                      228.0   \n",
       "3                                      228.0   \n",
       "4                                      192.0   \n",
       "\n",
       "   Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "0                                                2.5     \n",
       "1                                                2.5     \n",
       "2                                                0.0     \n",
       "3                                                0.0     \n",
       "4                                                0.0     \n",
       "\n",
       "   Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "0                                             1040.0      \n",
       "1                                             1055.0      \n",
       "2                                              932.0      \n",
       "3                                              932.0      \n",
       "4                                              978.4      \n",
       "\n",
       "   Fine Aggregate (component 7)(kg in a m^3 mixture)  Age (day)  \\\n",
       "0                                              676.0       28.0   \n",
       "1                                              676.0       28.0   \n",
       "2                                              594.0      270.0   \n",
       "3                                              594.0      365.0   \n",
       "4                                              825.5      360.0   \n",
       "\n",
       "   Concrete compressive strength(MPa, megapascals)   \n",
       "0                                             79.99  \n",
       "1                                             61.89  \n",
       "2                                             40.27  \n",
       "3                                             41.05  \n",
       "4                                             44.30  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age (day)']=df['Age (day)'].astype('float64')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cement (component 1)(kg in a m^3 mixture)                float64\n",
       "Blast Furnace Slag (component 2)(kg in a m^3 mixture)    float64\n",
       "Fly Ash (component 3)(kg in a m^3 mixture)               float64\n",
       "Water  (component 4)(kg in a m^3 mixture)                float64\n",
       "Superplasticizer (component 5)(kg in a m^3 mixture)      float64\n",
       "Coarse Aggregate  (component 6)(kg in a m^3 mixture)     float64\n",
       "Fine Aggregate (component 7)(kg in a m^3 mixture)        float64\n",
       "Age (day)                                                float64\n",
       "Concrete compressive strength(MPa, megapascals)          float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       79.99\n",
       "1       61.89\n",
       "2       40.27\n",
       "3       41.05\n",
       "4       44.30\n",
       "        ...  \n",
       "1025    44.28\n",
       "1026    31.18\n",
       "1027    23.70\n",
       "1028    32.77\n",
       "1029    32.40\n",
       "Name: Concrete compressive strength(MPa, megapascals) , Length: 1030, dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Concrete compressive strength(MPa, megapascals) ']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 45., 133., 156., 181., 196., 112., 100.,  52.,  36.,  19.]),\n",
       " array([ 2.33 , 10.357, 18.384, 26.411, 34.438, 42.465, 50.492, 58.519,\n",
       "        66.546, 74.573, 82.6  ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.style.use('seaborn-white')\n",
    "\n",
    "plt.hist(df['Concrete compressive strength(MPa, megapascals) '])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Splitting data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((515, 8), (515,), (309, 8), (309,), (206, 8), (206, 8))"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data= df.iloc[:515,:8]\n",
    "train_label=df.iloc[:515,8]\n",
    "\n",
    "test_data=df.iloc[515:824,:8]\n",
    "test_label=df.iloc[515:824,8]\n",
    "\n",
    "val_data=df.iloc[824:,:8]\n",
    "val_label=df.iloc[824:,:8]\n",
    "\n",
    "train_data.shape , train_label.shape , test_data.shape , test_label.shape , val_data.shape , val_label.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>Cement (component 1)(kg in a m^3 mixture)</th>\n",
       "      <th>Blast Furnace Slag (component 2)(kg in a m^3 mixture)</th>\n",
       "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
       "      <th>Water  (component 4)(kg in a m^3 mixture)</th>\n",
       "      <th>Superplasticizer (component 5)(kg in a m^3 mixture)</th>\n",
       "      <th>Coarse Aggregate  (component 6)(kg in a m^3 mixture)</th>\n",
       "      <th>Fine Aggregate (component 7)(kg in a m^3 mixture)</th>\n",
       "      <th>Age (day)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>540.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>676.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>540.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1055.0</td>\n",
       "      <td>676.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>332.5</td>\n",
       "      <td>142.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>932.0</td>\n",
       "      <td>594.0</td>\n",
       "      <td>270.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>332.5</td>\n",
       "      <td>142.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>932.0</td>\n",
       "      <td>594.0</td>\n",
       "      <td>365.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>198.6</td>\n",
       "      <td>132.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>978.4</td>\n",
       "      <td>825.5</td>\n",
       "      <td>360.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "0                                      540.0   \n",
       "1                                      540.0   \n",
       "2                                      332.5   \n",
       "3                                      332.5   \n",
       "4                                      198.6   \n",
       "\n",
       "   Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "0                                                0.0       \n",
       "1                                                0.0       \n",
       "2                                              142.5       \n",
       "3                                              142.5       \n",
       "4                                              132.4       \n",
       "\n",
       "   Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "0                                         0.0   \n",
       "1                                         0.0   \n",
       "2                                         0.0   \n",
       "3                                         0.0   \n",
       "4                                         0.0   \n",
       "\n",
       "   Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "0                                      162.0   \n",
       "1                                      162.0   \n",
       "2                                      228.0   \n",
       "3                                      228.0   \n",
       "4                                      192.0   \n",
       "\n",
       "   Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "0                                                2.5     \n",
       "1                                                2.5     \n",
       "2                                                0.0     \n",
       "3                                                0.0     \n",
       "4                                                0.0     \n",
       "\n",
       "   Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "0                                             1040.0      \n",
       "1                                             1055.0      \n",
       "2                                              932.0      \n",
       "3                                              932.0      \n",
       "4                                              978.4      \n",
       "\n",
       "   Fine Aggregate (component 7)(kg in a m^3 mixture)  Age (day)  \n",
       "0                                              676.0       28.0  \n",
       "1                                              676.0       28.0  \n",
       "2                                              594.0      270.0  \n",
       "3                                              594.0      365.0  \n",
       "4                                              825.5      360.0  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      79.99\n",
       "1      61.89\n",
       "2      40.27\n",
       "3      41.05\n",
       "4      44.30\n",
       "       ...  \n",
       "510    39.00\n",
       "511    65.70\n",
       "512    32.11\n",
       "513    40.29\n",
       "514    74.36\n",
       "Name: Concrete compressive strength(MPa, megapascals) , Length: 515, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Stadarization\n",
    "mean = np.mean(train_data)\n",
    "std = np.std(train_data)\n",
    "\n",
    "\n",
    "train_data -= mean\n",
    "train_data /= std\n",
    "\n",
    "val_data -= mean\n",
    "val_data /= std\n",
    "\n",
    "test_data -= mean\n",
    "test_data /= std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cement (component 1)(kg in a m^3 mixture)</th>\n",
       "      <th>Blast Furnace Slag (component 2)(kg in a m^3 mixture)</th>\n",
       "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
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       "      <td>1.208336</td>\n",
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       "      <th>511</th>\n",
       "      <td>1.208336</td>\n",
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       "      <td>-0.338208</td>\n",
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       "      <th>512</th>\n",
       "      <td>1.208336</td>\n",
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       "      <td>0.991494</td>\n",
       "      <td>-0.231061</td>\n",
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       "      <th>513</th>\n",
       "      <td>1.208336</td>\n",
       "      <td>-0.554527</td>\n",
       "      <td>0.991494</td>\n",
       "      <td>-0.231061</td>\n",
       "      <td>0.047596</td>\n",
       "      <td>-2.134066</td>\n",
       "      <td>-0.338208</td>\n",
       "      <td>-0.663018</td>\n",
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       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>1.208336</td>\n",
       "      <td>-0.554527</td>\n",
       "      <td>0.991494</td>\n",
       "      <td>-0.231061</td>\n",
       "      <td>0.047596</td>\n",
       "      <td>-2.134066</td>\n",
       "      <td>-0.338208</td>\n",
       "      <td>0.046475</td>\n",
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      "text/plain": [
       "     Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "510                                   1.208336   \n",
       "511                                   1.208336   \n",
       "512                                   1.208336   \n",
       "513                                   1.208336   \n",
       "514                                   1.208336   \n",
       "\n",
       "     Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "510                                          -0.554527       \n",
       "511                                          -0.554527       \n",
       "512                                          -0.554527       \n",
       "513                                          -0.554527       \n",
       "514                                          -0.554527       \n",
       "\n",
       "     Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "510                                    0.991494   \n",
       "511                                    0.991494   \n",
       "512                                    0.991494   \n",
       "513                                    0.991494   \n",
       "514                                    0.991494   \n",
       "\n",
       "     Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "510                                   0.174213   \n",
       "511                                   0.174213   \n",
       "512                                  -0.231061   \n",
       "513                                  -0.231061   \n",
       "514                                  -0.231061   \n",
       "\n",
       "     Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "510                                          -0.020163     \n",
       "511                                          -0.020163     \n",
       "512                                           0.047596     \n",
       "513                                           0.047596     \n",
       "514                                           0.047596     \n",
       "\n",
       "     Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "510                                          -2.134066      \n",
       "511                                          -2.134066      \n",
       "512                                          -2.134066      \n",
       "513                                          -2.134066      \n",
       "514                                          -2.134066      \n",
       "\n",
       "     Fine Aggregate (component 7)(kg in a m^3 mixture)  Age (day)  \n",
       "510                                          -0.338208  -0.663018  \n",
       "511                                          -0.338208   0.046475  \n",
       "512                                          -0.338208  -0.720936  \n",
       "513                                          -0.338208  -0.663018  \n",
       "514                                          -0.338208   0.046475  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Cement (component 1)(kg in a m^3 mixture)</th>\n",
       "      <th>Blast Furnace Slag (component 2)(kg in a m^3 mixture)</th>\n",
       "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
       "      <th>Water  (component 4)(kg in a m^3 mixture)</th>\n",
       "      <th>Superplasticizer (component 5)(kg in a m^3 mixture)</th>\n",
       "      <th>Coarse Aggregate  (component 6)(kg in a m^3 mixture)</th>\n",
       "      <th>Fine Aggregate (component 7)(kg in a m^3 mixture)</th>\n",
       "      <th>Age (day)</th>\n",
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       "      <th>819</th>\n",
       "      <td>2.175650</td>\n",
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       "      <td>0.620014</td>\n",
       "      <td>-1.460049</td>\n",
       "      <td>1.956593</td>\n",
       "      <td>-1.930310</td>\n",
       "      <td>0.538776</td>\n",
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       "      <th>820</th>\n",
       "      <td>2.175650</td>\n",
       "      <td>-0.84436</td>\n",
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       "      <td>0.620014</td>\n",
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       "      <td>1.956593</td>\n",
       "      <td>-1.930310</td>\n",
       "      <td>3.145077</td>\n",
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       "    <tr>\n",
       "      <th>821</th>\n",
       "      <td>0.231443</td>\n",
       "      <td>-0.84436</td>\n",
       "      <td>-1.115667</td>\n",
       "      <td>1.187397</td>\n",
       "      <td>-1.460049</td>\n",
       "      <td>-0.081986</td>\n",
       "      <td>0.242851</td>\n",
       "      <td>-0.561662</td>\n",
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       "    <tr>\n",
       "      <th>822</th>\n",
       "      <td>0.231443</td>\n",
       "      <td>-0.84436</td>\n",
       "      <td>-1.115667</td>\n",
       "      <td>1.187397</td>\n",
       "      <td>-1.460049</td>\n",
       "      <td>-0.081986</td>\n",
       "      <td>0.242851</td>\n",
       "      <td>-0.358950</td>\n",
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       "    <tr>\n",
       "      <th>823</th>\n",
       "      <td>0.231443</td>\n",
       "      <td>-0.84436</td>\n",
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       "      <td>1.187397</td>\n",
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       "      <td>0.242851</td>\n",
       "      <td>1.841926</td>\n",
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      "text/plain": [
       "     Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "819                                   2.175650   \n",
       "820                                   2.175650   \n",
       "821                                   0.231443   \n",
       "822                                   0.231443   \n",
       "823                                   0.231443   \n",
       "\n",
       "     Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "819                                           -0.84436       \n",
       "820                                           -0.84436       \n",
       "821                                           -0.84436       \n",
       "822                                           -0.84436       \n",
       "823                                           -0.84436       \n",
       "\n",
       "     Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "819                                   -1.115667   \n",
       "820                                   -1.115667   \n",
       "821                                   -1.115667   \n",
       "822                                   -1.115667   \n",
       "823                                   -1.115667   \n",
       "\n",
       "     Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "819                                   0.620014   \n",
       "820                                   0.620014   \n",
       "821                                   1.187397   \n",
       "822                                   1.187397   \n",
       "823                                   1.187397   \n",
       "\n",
       "     Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "819                                          -1.460049     \n",
       "820                                          -1.460049     \n",
       "821                                          -1.460049     \n",
       "822                                          -1.460049     \n",
       "823                                          -1.460049     \n",
       "\n",
       "     Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "819                                           1.956593      \n",
       "820                                           1.956593      \n",
       "821                                          -0.081986      \n",
       "822                                          -0.081986      \n",
       "823                                          -0.081986      \n",
       "\n",
       "     Fine Aggregate (component 7)(kg in a m^3 mixture)  Age (day)  \n",
       "819                                          -1.930310   0.538776  \n",
       "820                                          -1.930310   3.145077  \n",
       "821                                           0.242851  -0.561662  \n",
       "822                                           0.242851  -0.358950  \n",
       "823                                           0.242851   1.841926  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Cement (component 1)(kg in a m^3 mixture)</th>\n",
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       "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
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       "      <th>1025</th>\n",
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       "      <th>1026</th>\n",
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       "      <td>0.903705</td>\n",
       "      <td>0.301694</td>\n",
       "      <td>-2.189418</td>\n",
       "      <td>0.398575</td>\n",
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       "    <tr>\n",
       "      <th>1027</th>\n",
       "      <td>-1.430231</td>\n",
       "      <td>0.992126</td>\n",
       "      <td>0.617952</td>\n",
       "      <td>0.769965</td>\n",
       "      <td>-0.426719</td>\n",
       "      <td>-1.183629</td>\n",
       "      <td>0.010427</td>\n",
       "      <td>-0.35895</td>\n",
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       "      <th>1028</th>\n",
       "      <td>-1.328711</td>\n",
       "      <td>1.615266</td>\n",
       "      <td>-1.115667</td>\n",
       "      <td>0.076947</td>\n",
       "      <td>0.454152</td>\n",
       "      <td>0.128622</td>\n",
       "      <td>0.113856</td>\n",
       "      <td>-0.35895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1029</th>\n",
       "      <td>-0.353734</td>\n",
       "      <td>0.479649</td>\n",
       "      <td>0.134263</td>\n",
       "      <td>1.090131</td>\n",
       "      <td>-0.003224</td>\n",
       "      <td>-1.560294</td>\n",
       "      <td>-0.204564</td>\n",
       "      <td>-0.35895</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "1025                                  -0.205285   \n",
       "1026                                   0.233359   \n",
       "1027                                  -1.430231   \n",
       "1028                                  -1.328711   \n",
       "1029                                  -0.353734   \n",
       "\n",
       "      Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "1025                                           0.683849       \n",
       "1026                                          -0.844360       \n",
       "1027                                           0.992126       \n",
       "1028                                           1.615266       \n",
       "1029                                           0.479649       \n",
       "\n",
       "      Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "1025                                    0.325823   \n",
       "1026                                    0.729695   \n",
       "1027                                    0.617952   \n",
       "1028                                   -1.115667   \n",
       "1029                                    0.134263   \n",
       "\n",
       "      Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "1025                                   0.239056   \n",
       "1026                                   0.903705   \n",
       "1027                                   0.769965   \n",
       "1028                                   0.076947   \n",
       "1029                                   1.090131   \n",
       "\n",
       "      Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "1025                                           0.047596     \n",
       "1026                                           0.301694     \n",
       "1027                                          -0.426719     \n",
       "1028                                           0.454152     \n",
       "1029                                          -0.003224     \n",
       "\n",
       "      Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "1025                                          -1.484691      \n",
       "1026                                          -2.189418      \n",
       "1027                                          -1.183629      \n",
       "1028                                           0.128622      \n",
       "1029                                          -1.560294      \n",
       "\n",
       "      Fine Aggregate (component 7)(kg in a m^3 mixture)  Age (day)  \n",
       "1025                                          -0.125540   -0.35895  \n",
       "1026                                           0.398575   -0.35895  \n",
       "1027                                           0.010427   -0.35895  \n",
       "1028                                           0.113856   -0.35895  \n",
       "1029                                          -0.204564   -0.35895  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val_data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import models\n",
    "from keras import layers\n",
    "def build_model():\n",
    "    model = models.Sequential()\n",
    "    model.add(layers.Dense(10, activation='relu',input_shape=(train_data.shape[1],)))\n",
    "    model.add(layers.Dense(8, activation='relu'))\n",
    "    model.add(layers.Dense(6, activation='relu'))\n",
    "    model.add(layers.Dense(1))\n",
    "    model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "263.41485595703125"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.fit(train_data, train_label,epochs=100, batch_size=1, verbose=0)\n",
    "mse , mae = model.evaluate(val_data, val_label, verbose=0)\n",
    "mae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Over-fitting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Epoch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = build_model()\n",
    "history = model.fit(train_data, train_label,epochs=500, batch_size=16, verbose=0,validation_data=(val_data, val_label))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['loss', 'mae', 'val_loss', 'val_mae'])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loss = history.history['mae']\n",
    "val_loss = history.history['val_mae']\n",
    "epochs= range(500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(epochs, train_loss, 'r', label='Training mae')\n",
    "plt.plot(epochs, val_loss, 'g', label='Validation mae')\n",
    "plt.title('Training and Validation loss ')\n",
    "plt.xlabel('Epochs')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "it appears after a few epochs, the mae loss becomes constant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# No. of Layers & Memory Capacity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import models\n",
    "from keras import layers\n",
    "def build_model():\n",
    "    model = models.Sequential()\n",
    "    model.add(layers.Dense(14, activation='relu',input_shape=(train_data.shape[1],)))\n",
    "    model.add(layers.Dense(4, activation='relu'))\n",
    "    model.add(layers.Dense(4, activation='relu'))\n",
    "    model.add(layers.Dense(1))\n",
    "    model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "265.8184814453125"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.fit(train_data, train_label,epochs=100, batch_size=1, verbose=0)\n",
    "mse , mae = model.evaluate(val_data, val_label, verbose=0)\n",
    "mae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8-8-6= 267.6055908203125"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10-6= 267.1843566894531\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10-4-4= 266.9336242675781\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10-6-4= 265.1640930175781\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14-4-4=264.3193664550781  #best one so far\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14-8-6=265.1615905761719"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# activation function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import models\n",
    "from keras import layers\n",
    "def build_model():\n",
    "    model = models.Sequential()\n",
    "    model.add(layers.Dense(10, activation='tanh',input_shape=(train_data.shape[1],)))\n",
    "    model.add(layers.Dense(8, activation='tanh'))\n",
    "    model.add(layers.Dense(6, activation='tanh'))\n",
    "    model.add(layers.Dense(1))\n",
    "    model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "266.0728454589844"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.fit(train_data, train_label,epochs=100, batch_size=1, verbose=0)\n",
    "mse , mae = model.evaluate(val_data, val_label, verbose=0)\n",
    "mae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14-4-4=266.08599853515625"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "so no need of changing the activation function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regulizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import regularizers\n",
    "from keras import models\n",
    "from keras import layers\n",
    "def build_model():\n",
    "    model = models.Sequential()\n",
    "    model.add(layers.Dense(14, kernel_regularizer=regularizers.l2(0.001), activation='relu',input_shape=(train_data.shape[1],)))\n",
    "    model.add(layers.Dense(4, kernel_regularizer=regularizers.l2(0.001), activation='relu'))\n",
    "    model.add(layers.Dense(4, kernel_regularizer=regularizers.l2(0.001), activation='relu'))\n",
    "    model.add(layers.Dense(1))\n",
    "    model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "268.10162353515625"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.fit(train_data, train_label,epochs=100, batch_size=1, verbose=0)\n",
    "mse , mae = model.evaluate(val_data, val_label, verbose=0)\n",
    "mae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " l2(0.001)=264.28607177734375"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "l1(0.001)=266.1231689453125\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import models\n",
    "from keras import layers\n",
    "def build_model():\n",
    "    model = models.Sequential()\n",
    "    model.add(layers.Dense(14, activation='relu',input_shape=(train_data.shape[1],)))\n",
    "    model.add(layers.Dropout(0.2))\n",
    "    model.add(layers.Dense(4, activation='relu'))\n",
    "    model.add(layers.Dropout(0.2))\n",
    "    model.add(layers.Dense(4, activation='relu'))\n",
    "    model.add(layers.Dropout(0.2))\n",
    "    model.add(layers.Dense(1))\n",
    "    model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "268.2809753417969"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.fit(train_data, train_label,epochs=100, batch_size=1, verbose=0)\n",
    "mse , mae = model.evaluate(val_data, val_label, verbose=0)\n",
    "mae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dropout(0.5)=268.9576721191406"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dropout(0.2)=268.2809753417969"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import regularizers\n",
    "from keras import models\n",
    "from keras import layers\n",
    "def build_model():\n",
    "    model = models.Sequential()\n",
    "    model.add(layers.Dense(10, kernel_regularizer=regularizers.l2(0.001), activation='relu',input_shape=(train_data.shape[1],)))\n",
    "    model.add(layers.Dense(8, kernel_regularizer=regularizers.l2(0.001), activation='relu'))\n",
    "    model.add(layers.Dense(6, kernel_regularizer=regularizers.l2(0.001), activation='relu'))\n",
    "    model.add(layers.Dense(1))\n",
    "    model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "264.6249084472656"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = build_model()\n",
    "model.fit(train_data, train_label,epochs=100, batch_size=1, verbose=0)\n",
    "mse , mae = model.evaluate(val_data, val_label, verbose=0)\n",
    "mae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = model.predict(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(309, 1)"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_df = pd.DataFrame({'Actual': test_label, 'Prediction': np.round(predictions.reshape(309))})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "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>Actual</th>\n",
       "      <th>Prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>21.97</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>9.85</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>15.07</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>23.25</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>43.73</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>819</th>\n",
       "      <td>58.78</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>820</th>\n",
       "      <td>67.11</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>821</th>\n",
       "      <td>20.77</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>822</th>\n",
       "      <td>25.18</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>823</th>\n",
       "      <td>29.59</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>309 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Actual  Prediction\n",
       "515   21.97        28.0\n",
       "516    9.85        17.0\n",
       "517   15.07        17.0\n",
       "518   23.25        32.0\n",
       "519   43.73        49.0\n",
       "..      ...         ...\n",
       "819   58.78        59.0\n",
       "820   67.11        67.0\n",
       "821   20.77        21.0\n",
       "822   25.18        31.0\n",
       "823   29.59        52.0\n",
       "\n",
       "[309 rows x 2 columns]"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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