Backward_Elimination_Wrapper_Feature_Seletion_Method.ipynb

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    "id": "ZiWdDezL7WVm"
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.datasets import load_breast_cancer\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "from mlxtend.plotting import plot_sequential_feature_selection\n",
    "from sklearn.feature_selection import SequentialFeatureSelector\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings ('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "FKsHNioQ73LZ"
   },
   "outputs": [],
   "source": [
    "# Load the breast cancer dataset\n",
    "data = load_breast_cancer()\n",
    "X = data.data\n",
    "y = data.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "syNpjUHU0iMr"
   },
   "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": 4,
   "metadata": {
    "id": "tLOBWgOp0jmt"
   },
   "outputs": [],
   "source": [
    "base_model= LogisticRegression()"
   ]
  },
  {
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   "execution_count": 5,
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   "outputs": [
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      ],
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       "LogisticRegression()"
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     "execution_count": 5,
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    "base_model.fit(X_train,y_train)"
   ]
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     "execution_count": 6,
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   "source": [
    "base_model_score= base_model.score(X_test,y_test)\n",
    "base_model_score"
   ]
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "mdnLqPrG1Y_T"
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   "source": [
    "selector= SequentialFeatureSelector(base_model,n_features_to_select=5,direction= 'backward',scoring= 'accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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   "source": [
    "selector=selector.fit(X_train,y_train)"
   ]
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   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "GZSCodh2154U"
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   "source": [
    "selected_features= selector.get_support(indices=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "ssriQi312Tmp"
   },
   "outputs": [],
   "source": [
    "X_train_selected= selector.transform(X_train)\n",
    "X_test_selected= selector.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "Bsd29M1r2V1X"
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   "outputs": [],
   "source": [
    "final_model= LogisticRegression()"
   ]
  },
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   "execution_count": 12,
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      ],
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_model.fit(X_train_selected,y_train)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "yYtN2D0c3LcO"
   },
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   "source": [
    "final_model_score= final_model.score(X_test_selected,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
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    },
    "id": "1cVoIMH83T2C",
    "outputId": "faf4d435-d11d-489c-facc-39e75c16d070"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9385964912280702"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_model_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "qwbc9q7q3WmH",
    "outputId": "f38e4e19-96fe-4cda-d320-24524e11b235"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_selected.shape[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "qcvaNHSX3cIh",
    "outputId": "a78eb004-97a2-4458-ab3b-aea9484319a3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "goWUi3gf3flH"
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import "
   ]
  }
 ],
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