11[SVM for digits dataset].ipynb

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   "execution_count": 12,
   "id": "2feaaf50-9429-4a22-84e1-208bad26e421",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_digits\n",
    "import pandas as pd\n",
    "digits = load_digits()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f799f2c2-de18-4459-9af0-2d7f81048b45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DESCR', 'data', 'feature_names', 'frame', 'images', 'target', 'target_names']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(digits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9dd7f802-3c90-42c6-a583-64ea94999fcf",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "array([0, 1, 2, ..., 8, 9, 8])"
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "digits.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6574350a-9023-427c-b689-b25f39bda277",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = digits.data\n",
    "y= digits.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f86a2430-3369-4f0c-aa67-c07d1b15fd28",
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       "\n",
       "[1797 rows x 65 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(digits.data, digits.target)\n",
    "df['target'] = digits.target\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a7976455-1599-482a-9fa0-19d91043672f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.svm import SVC\n",
    "X_train, X_test, y_train, y_test = train_test_split(df.drop('target',axis='columns'), df.target, test_size=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "50f8c728-0105-433a-a1c4-30d73988ea36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9814814814814815"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##using rbf\n",
    "model_rbf = SVC(kernel='rbf')\n",
    "model_rbf.fit(X_train, y_train)\n",
    "model_rbf.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d48837e3-7957-44ca-a945-201790ea30bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.975925925925926"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##using linear\n",
    "model_linear = SVC(kernel='linear')\n",
    "model_linear.fit(X_train, y_train)\n",
    "model_linear.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a73ce2fc-cbb5-4494-8664-d6be55ce75cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "##using rbf\n",
    "model_rbf = SVC(kernel='rbf')\n",
    "model_rbf.fit(X_train, y_train)\n",
    "model_rbf.score(X_test, y_test)"
   ]
  }
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