1-6-RandomForestRegressor-vs-DecisionTreeRegressor.ipynb

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    "<div class=\"alert alert-block alert-success\">\n",
    "    <b><h2>RandomForestRegressor vs DecisionTreeRegressor</h2></b> \n",
    "    <ul>\n",
    "    <li> Bu bölümde iki ağaç algoritmasını karşılaştıracağız\n",
    "    <li> Daha önceki bölümlerde görmüştük. Rassal orman algoritması Karar ağaçları ile oluşturulan bir algoritma idi\n",
    "    </ul>\n",
    "    <img src=\"https://user-images.githubusercontent.com/45025357/53289359-3343bc80-37bb-11e9-86d1-f78673687821.jpg\" width=400 />\n",
    "    <b><h3>Model karşılaştırmada kullanılan parametre ve değerler</h3></b>\n",
    "    <ul>\n",
    "          <ul>\n",
    "        <li><b>1. Karşılaştırma</b><ul>\n",
    "            <li><b>Tüm parametreler default ayarlı</b>\n",
    "          </ul></ul>\n",
    "          <ul><li><b>2. Karşılaştırma</b> \n",
    "              <ul>\n",
    "        <li><b>max_depth:</b> 15\n",
    "          </ul> </ul>\n",
    "    </ul>\n",
    "    <img src=\"https://qph.fs.quoracdn.net/main-qimg-1ec0ae202b49683e52b995a1563476d8\"  width=300/>\n",
    "</div>\n",
    "\n",
    "#### Bu bölümde işlenecek konular\n",
    "\n",
    "1. [Default Model ve sonuç](#bir)\n",
    "2. [Max depth ile karşılaştırma](#bir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('./Data/home-data-for-ml-course/train.csv',index_col=\"Id\")"
   ]
  },
  {
   "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>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "Id                                                                    \n",
       "1           60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "2           20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "3           60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "4           70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "5           60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "   LandContour Utilities LotConfig  ... PoolArea PoolQC Fence MiscFeature  \\\n",
       "Id                                  ...                                     \n",
       "1          Lvl    AllPub    Inside  ...        0    NaN   NaN         NaN   \n",
       "2          Lvl    AllPub       FR2  ...        0    NaN   NaN         NaN   \n",
       "3          Lvl    AllPub    Inside  ...        0    NaN   NaN         NaN   \n",
       "4          Lvl    AllPub    Corner  ...        0    NaN   NaN         NaN   \n",
       "5          Lvl    AllPub       FR2  ...        0    NaN   NaN         NaN   \n",
       "\n",
       "   MiscVal MoSold  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "Id                                                             \n",
       "1        0      2    2008        WD         Normal     208500  \n",
       "2        0      5    2007        WD         Normal     181500  \n",
       "3        0      9    2008        WD         Normal     223500  \n",
       "4        0      2    2006        WD        Abnorml     140000  \n",
       "5        0     12    2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 80 columns]"
      ]
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['MSSubClass', 'MSZoning', 'LotFrontage', 'LotArea', 'Street', 'Alley',\n",
       "       'LotShape', 'LandContour', 'Utilities', 'LotConfig', 'LandSlope',\n",
       "       'Neighborhood', 'Condition1', 'Condition2', 'BldgType', 'HouseStyle',\n",
       "       'OverallQual', 'OverallCond', 'YearBuilt', 'YearRemodAdd', 'RoofStyle',\n",
       "       'RoofMatl', 'Exterior1st', 'Exterior2nd', 'MasVnrType', 'MasVnrArea',\n",
       "       'ExterQual', 'ExterCond', 'Foundation', 'BsmtQual', 'BsmtCond',\n",
       "       'BsmtExposure', 'BsmtFinType1', 'BsmtFinSF1', 'BsmtFinType2',\n",
       "       'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF', 'Heating', 'HeatingQC',\n",
       "       'CentralAir', 'Electrical', '1stFlrSF', '2ndFlrSF', 'LowQualFinSF',\n",
       "       'GrLivArea', 'BsmtFullBath', 'BsmtHalfBath', 'FullBath', 'HalfBath',\n",
       "       'BedroomAbvGr', 'KitchenAbvGr', 'KitchenQual', 'TotRmsAbvGrd',\n",
       "       'Functional', 'Fireplaces', 'FireplaceQu', 'GarageType', 'GarageYrBlt',\n",
       "       'GarageFinish', 'GarageCars', 'GarageArea', 'GarageQual', 'GarageCond',\n",
       "       'PavedDrive', 'WoodDeckSF', 'OpenPorchSF', 'EnclosedPorch', '3SsnPorch',\n",
       "       'ScreenPorch', 'PoolArea', 'PoolQC', 'Fence', 'MiscFeature', 'MiscVal',\n",
       "       'MoSold', 'YrSold', 'SaleType', 'SaleCondition', 'SalePrice'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_cols=[item for item in data.columns if data[item].dtype in ['int64','float64']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=data[num_cols].drop(columns=\"SalePrice\")\n",
    "y=data.SalePrice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=X.apply(lambda x: x.fillna(x.mean()),axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id=\"bir\"  style=\"color:blue;\"> 1. Default model karşılaştırma</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTreeRegressor MAE 27029.134246575344\n",
      "RandomForestRegressor MAE 16655.009552511416\n"
     ]
    }
   ],
   "source": [
    "model_dt=DecisionTreeRegressor(random_state=0)\n",
    "model_dt.fit(X_train,y_train)\n",
    "pred_dt=model_dt.predict(X_test)\n",
    "print(\"DecisionTreeRegressor MAE\",mean_absolute_error(y_test,pred_dt))\n",
    "\n",
    "model_rf=RandomForestRegressor(random_state=0)\n",
    "model_rf.fit(X_train,y_train)\n",
    "pred_rf=model_rf.predict(X_test)\n",
    "print(\"RandomForestRegressor MAE\",mean_absolute_error(y_test,pred_rf))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div id=\"iki\"  style=\"color:blue;\"> 2. Model karşılaştırma </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTreeRegressor MAE 24699.71086757991\n",
      "RandomForestRegressor MAE 16560.944584477336\n"
     ]
    }
   ],
   "source": [
    "model_dt=DecisionTreeRegressor(max_depth=15,random_state=0)\n",
    "model_dt.fit(X_train,y_train)\n",
    "pred_dt2=model_dt.predict(X_test)\n",
    "print(\"DecisionTreeRegressor MAE\",mean_absolute_error(y_test,pred_dt2))\n",
    "\n",
    "model_rf=RandomForestRegressor(max_depth=15,random_state=0)\n",
    "model_rf.fit(X_train,y_train)\n",
    "pred_rf2=model_rf.predict(X_test)\n",
    "print(\"RandomForestRegressor MAE\",mean_absolute_error(y_test,pred_rf2))"
   ]
  }
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