diff --git a/11_deep_learning.ipynb b/11_deep_learning.ipynb
index 29b394c..4bac782 100644
--- a/11_deep_learning.ipynb
+++ b/11_deep_learning.ipynb
@@ -11,12 +11,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPython 3.5.5\n",
-      "IPython 6.3.0\n",
+      "CPython 3.6.5\n",
+      "IPython 6.4.0\n",
       "\n",
       "numpy 1.14.3\n",
       "sklearn 0.19.1\n",
-      "scipy 1.0.1\n",
+      "scipy 1.1.0\n",
       "matplotlib 2.2.2\n",
       "tensorflow 1.8.0\n"
      ]
@@ -386,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -401,7 +401,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -415,20 +415,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
-      "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
-      "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
-      "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# from tensorflow.examples.tutorials.mnist import input_data\n",
     "# mnist = input_data.read_data_sets(\"/tmp/data/\")"
@@ -436,7 +425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 22,
    "metadata": {
     "scrolled": true
    },
@@ -445,14 +434,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 배치 정확도: 0.86 검증 세트 정확도: 0.9044\n",
-      "5 배치 정확도: 0.94 검증 세트 정확도: 0.951\n",
-      "10 배치 정확도: 0.96 검증 세트 정확도: 0.9662\n",
-      "15 배치 정확도: 1.0 검증 세트 정확도: 0.9722\n",
-      "20 배치 정확도: 1.0 검증 세트 정확도: 0.9746\n",
-      "25 배치 정확도: 1.0 검증 세트 정확도: 0.9764\n",
-      "30 배치 정확도: 0.98 검증 세트 정확도: 0.978\n",
-      "35 배치 정확도: 0.96 검증 세트 정확도: 0.9794\n"
+      "0 배치 데이터 정확도: 0.86 검증 세트 정확도: 0.9048\n",
+      "5 배치 데이터 정확도: 0.94 검증 세트 정확도: 0.9492\n",
+      "10 배치 데이터 정확도: 0.92 검증 세트 정확도: 0.9656\n",
+      "15 배치 데이터 정확도: 0.94 검증 세트 정확도: 0.971\n",
+      "20 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9766\n",
+      "25 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9772\n",
+      "30 배치 데이터 정확도: 0.98 검증 세트 정확도: 0.9782\n",
+      "35 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9786\n"
      ]
     }
    ],
@@ -482,7 +471,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -492,7 +481,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -528,7 +517,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -539,7 +528,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -562,7 +551,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -574,7 +563,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -610,7 +599,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -652,7 +641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -678,7 +667,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -726,21 +715,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 배치 정확도: 0.96 검증 세트 정확도: 0.924\n",
-      "5 배치 정확도: 1.0 검증 세트 정확도: 0.9568\n",
-      "10 배치 정확도: 0.94 검증 세트 정확도: 0.967\n",
-      "15 배치 정확도: 0.98 검증 세트 정확도: 0.9686\n",
-      "20 배치 정확도: 1.0 검증 세트 정확도: 0.971\n",
-      "25 배치 정확도: 1.0 검증 세트 정확도: 0.9694\n",
-      "30 배치 정확도: 1.0 검증 세트 정확도: 0.97\n",
-      "35 배치 정확도: 1.0 검증 세트 정확도: 0.9712\n"
+      "0 배치 데이터 정확도: 0.88 검증 세트 정확도: 0.9232\n",
+      "5 배치 데이터 정확도: 0.98 검증 세트 정확도: 0.9574\n",
+      "10 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9662\n",
+      "15 배치 데이터 정확도: 0.96 검증 세트 정확도: 0.9684\n",
+      "20 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9692\n",
+      "25 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9692\n",
+      "30 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.9696\n",
+      "35 배치 데이터 정확도: 1.0 검증 세트 정확도: 0.97\n"
      ]
     }
    ],
@@ -781,7 +770,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -813,7 +802,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -832,7 +821,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -860,7 +849,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -916,7 +905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -926,33 +915,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.8666\n",
-      "1 테스트 정확도: 0.894\n",
-      "2 테스트 정확도: 0.9088\n",
-      "3 테스트 정확도: 0.9189\n",
-      "4 테스트 정확도: 0.9262\n",
-      "5 테스트 정확도: 0.9334\n",
-      "6 테스트 정확도: 0.9379\n",
-      "7 테스트 정확도: 0.9419\n",
-      "8 테스트 정확도: 0.9444\n",
-      "9 테스트 정확도: 0.9477\n",
-      "10 테스트 정확도: 0.9499\n",
-      "11 테스트 정확도: 0.952\n",
-      "12 테스트 정확도: 0.9546\n",
-      "13 테스트 정확도: 0.956\n",
-      "14 테스트 정확도: 0.9567\n",
-      "15 테스트 정확도: 0.9591\n",
-      "16 테스트 정확도: 0.9609\n",
-      "17 테스트 정확도: 0.9612\n",
-      "18 테스트 정확도: 0.9618\n",
-      "19 테스트 정확도: 0.9635\n"
+      "0 검증 세트 정확도: 0.9042\n",
+      "1 검증 세트 정확도: 0.928\n",
+      "2 검증 세트 정확도: 0.9374\n",
+      "3 검증 세트 정확도: 0.9474\n",
+      "4 검증 세트 정확도: 0.9532\n",
+      "5 검증 세트 정확도: 0.9572\n",
+      "6 검증 세트 정확도: 0.9626\n",
+      "7 검증 세트 정확도: 0.9628\n",
+      "8 검증 세트 정확도: 0.9664\n",
+      "9 검증 세트 정확도: 0.968\n",
+      "10 검증 세트 정확도: 0.9694\n",
+      "11 검증 세트 정확도: 0.9696\n",
+      "12 검증 세트 정확도: 0.971\n",
+      "13 검증 세트 정확도: 0.971\n",
+      "14 검증 세트 정확도: 0.9728\n",
+      "15 검증 세트 정확도: 0.9734\n",
+      "16 검증 세트 정확도: 0.9728\n",
+      "17 검증 세트 정확도: 0.975\n",
+      "18 검증 세트 정확도: 0.9752\n",
+      "19 검증 세트 정확도: 0.976\n"
      ]
     }
    ],
@@ -1008,7 +997,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -1028,7 +1017,7 @@
        " 'batch_normalization_2/beta:0']"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1039,7 +1028,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -1065,7 +1054,7 @@
        " 'batch_normalization_2/moving_variance:0']"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1090,7 +1079,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1122,7 +1111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1138,7 +1127,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1160,7 +1149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1171,7 +1160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1181,7 +1170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1191,33 +1180,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.3138\n",
-      "1 테스트 정확도: 0.8001\n",
-      "2 테스트 정확도: 0.881\n",
-      "3 테스트 정확도: 0.904\n",
-      "4 테스트 정확도: 0.9122\n",
-      "5 테스트 정확도: 0.9195\n",
-      "6 테스트 정확도: 0.9245\n",
-      "7 테스트 정확도: 0.9301\n",
-      "8 테스트 정확도: 0.9331\n",
-      "9 테스트 정확도: 0.9389\n",
-      "10 테스트 정확도: 0.943\n",
-      "11 테스트 정확도: 0.9449\n",
-      "12 테스트 정확도: 0.9456\n",
-      "13 테스트 정확도: 0.9485\n",
-      "14 테스트 정확도: 0.9524\n",
-      "15 테스트 정확도: 0.9519\n",
-      "16 테스트 정확도: 0.9563\n",
-      "17 테스트 정확도: 0.9583\n",
-      "18 테스트 정확도: 0.956\n",
-      "19 테스트 정확도: 0.9608\n"
+      "0 검증 세트 정확도: 0.288\n",
+      "1 검증 세트 정확도: 0.794\n",
+      "2 검증 세트 정확도: 0.8798\n",
+      "3 검증 세트 정확도: 0.906\n",
+      "4 검증 세트 정확도: 0.9164\n",
+      "5 검증 세트 정확도: 0.9214\n",
+      "6 검증 세트 정확도: 0.9292\n",
+      "7 검증 세트 정확도: 0.9358\n",
+      "8 검증 세트 정확도: 0.9382\n",
+      "9 검증 세트 정확도: 0.9414\n",
+      "10 검증 세트 정확도: 0.9456\n",
+      "11 검증 세트 정확도: 0.9472\n",
+      "12 검증 세트 정확도: 0.9476\n",
+      "13 검증 세트 정확도: 0.9534\n",
+      "14 검증 세트 정확도: 0.9566\n",
+      "15 검증 세트 정확도: 0.9566\n",
+      "16 검증 세트 정확도: 0.9576\n",
+      "17 검증 세트 정확도: 0.9586\n",
+      "18 검증 세트 정확도: 0.962\n",
+      "19 검증 세트 정확도: 0.9616\n"
      ]
     }
    ],
@@ -1256,7 +1245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1265,7 +1254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1281,7 +1270,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
@@ -1571,7 +1560,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1580,7 +1569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
@@ -1588,9 +1577,10 @@
       "text/html": [
        "\n",
        "        <iframe seamless style=\"width:1200px;height:620px;border:0\" srcdoc=\"\n",
+       "        <script src=&quot;//cdnjs.cloudflare.com/ajax/libs/polymer/0.3.3/platform.js&quot;></script>\n",
        "        <script>\n",
        "          function load() {\n",
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@@ -1621,7 +1611,7 @@
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+   "execution_count": 53,
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@@ -1642,7 +1632,7 @@
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+   "execution_count": 54,
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@@ -1659,7 +1649,7 @@
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+   "execution_count": 55,
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@@ -1675,7 +1665,7 @@
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+   "execution_count": 56,
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     {
@@ -1701,7 +1691,7 @@
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+   "execution_count": 57,
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     {
@@ -1709,26 +1699,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.9607\n",
-      "1 테스트 정확도: 0.9611\n",
-      "2 테스트 정확도: 0.962\n",
-      "3 테스트 정확도: 0.961\n",
-      "4 테스트 정확도: 0.9643\n",
-      "5 테스트 정확도: 0.9653\n",
-      "6 테스트 정확도: 0.9665\n",
-      "7 테스트 정확도: 0.9628\n",
-      "8 테스트 정확도: 0.9663\n",
-      "9 테스트 정확도: 0.967\n",
-      "10 테스트 정확도: 0.9668\n",
-      "11 테스트 정확도: 0.9674\n",
-      "12 테스트 정확도: 0.9675\n",
-      "13 테스트 정확도: 0.9682\n",
-      "14 테스트 정확도: 0.9688\n",
-      "15 테스트 정확도: 0.9685\n",
-      "16 테스트 정확도: 0.9687\n",
-      "17 테스트 정확도: 0.9701\n",
-      "18 테스트 정확도: 0.9678\n",
-      "19 테스트 정확도: 0.9687\n"
+      "0 검증 세트 정확도: 0.9632\n",
+      "1 검증 세트 정확도: 0.963\n",
+      "2 검증 세트 정확도: 0.9656\n",
+      "3 검증 세트 정확도: 0.965\n",
+      "4 검증 세트 정확도: 0.964\n",
+      "5 검증 세트 정확도: 0.965\n",
+      "6 검증 세트 정확도: 0.9688\n",
+      "7 검증 세트 정확도: 0.9684\n",
+      "8 검증 세트 정확도: 0.9684\n",
+      "9 검증 세트 정확도: 0.9686\n",
+      "10 검증 세트 정확도: 0.9702\n",
+      "11 검증 세트 정확도: 0.9712\n",
+      "12 검증 세트 정확도: 0.9674\n",
+      "13 검증 세트 정확도: 0.97\n",
+      "14 검증 세트 정확도: 0.971\n",
+      "15 검증 세트 정확도: 0.9724\n",
+      "16 검증 세트 정확도: 0.9718\n",
+      "17 검증 세트 정확도: 0.9712\n",
+      "18 검증 세트 정확도: 0.9712\n",
+      "19 검증 세트 정확도: 0.9714\n"
      ]
     }
    ],
@@ -1754,7 +1744,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1808,7 +1798,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [
     {
@@ -1816,26 +1806,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.9612\n",
-      "1 테스트 정확도: 0.9617\n",
-      "2 테스트 정확도: 0.9625\n",
-      "3 테스트 정확도: 0.9617\n",
-      "4 테스트 정확도: 0.9646\n",
-      "5 테스트 정확도: 0.9637\n",
-      "6 테스트 정확도: 0.9647\n",
-      "7 테스트 정확도: 0.9648\n",
-      "8 테스트 정확도: 0.9669\n",
-      "9 테스트 정확도: 0.968\n",
-      "10 테스트 정확도: 0.9678\n",
-      "11 테스트 정확도: 0.9678\n",
-      "12 테스트 정확도: 0.9687\n",
-      "13 테스트 정확도: 0.9686\n",
-      "14 테스트 정확도: 0.9685\n",
-      "15 테스트 정확도: 0.9694\n",
-      "16 테스트 정확도: 0.9682\n",
-      "17 테스트 정확도: 0.9694\n",
-      "18 테스트 정확도: 0.9695\n",
-      "19 테스트 정확도: 0.9707\n"
+      "0 검증 세트 정확도: 0.9642\n",
+      "1 검증 세트 정확도: 0.9628\n",
+      "2 검증 세트 정확도: 0.9654\n",
+      "3 검증 세트 정확도: 0.965\n",
+      "4 검증 세트 정확도: 0.9642\n",
+      "5 검증 세트 정확도: 0.965\n",
+      "6 검증 세트 정확도: 0.9684\n",
+      "7 검증 세트 정확도: 0.9684\n",
+      "8 검증 세트 정확도: 0.9686\n",
+      "9 검증 세트 정확도: 0.9684\n",
+      "10 검증 세트 정확도: 0.9702\n",
+      "11 검증 세트 정확도: 0.9712\n",
+      "12 검증 세트 정확도: 0.9674\n",
+      "13 검증 세트 정확도: 0.97\n",
+      "14 검증 세트 정확도: 0.9706\n",
+      "15 검증 세트 정확도: 0.9724\n",
+      "16 검증 세트 정확도: 0.9716\n",
+      "17 검증 세트 정확도: 0.9712\n",
+      "18 검증 세트 정확도: 0.9714\n",
+      "19 검증 세트 정확도: 0.9712\n"
      ]
     }
    ],
@@ -1861,7 +1851,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1905,7 +1895,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
@@ -1913,26 +1903,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.9236\n",
-      "1 테스트 정확도: 0.9383\n",
-      "2 테스트 정확도: 0.9492\n",
-      "3 테스트 정확도: 0.9526\n",
-      "4 테스트 정확도: 0.9566\n",
-      "5 테스트 정확도: 0.9577\n",
-      "6 테스트 정확도: 0.9596\n",
-      "7 테스트 정확도: 0.961\n",
-      "8 테스트 정확도: 0.9623\n",
-      "9 테스트 정확도: 0.9626\n",
-      "10 테스트 정확도: 0.9642\n",
-      "11 테스트 정확도: 0.9628\n",
-      "12 테스트 정확도: 0.9641\n",
-      "13 테스트 정확도: 0.9655\n",
-      "14 테스트 정확도: 0.9655\n",
-      "15 테스트 정확도: 0.9662\n",
-      "16 테스트 정확도: 0.9676\n",
-      "17 테스트 정확도: 0.9686\n",
-      "18 테스트 정확도: 0.9687\n",
-      "19 테스트 정확도: 0.9693\n"
+      "0 검증 세트 정확도: 0.9236\n",
+      "1 검증 세트 정확도: 0.9454\n",
+      "2 검증 세트 정확도: 0.953\n",
+      "3 검증 세트 정확도: 0.9582\n",
+      "4 검증 세트 정확도: 0.9608\n",
+      "5 검증 세트 정확도: 0.9562\n",
+      "6 검증 세트 정확도: 0.9626\n",
+      "7 검증 세트 정확도: 0.9628\n",
+      "8 검증 세트 정확도: 0.9642\n",
+      "9 검증 세트 정확도: 0.965\n",
+      "10 검증 세트 정확도: 0.9662\n",
+      "11 검증 세트 정확도: 0.9666\n",
+      "12 검증 세트 정확도: 0.9648\n",
+      "13 검증 세트 정확도: 0.9676\n",
+      "14 검증 세트 정확도: 0.968\n",
+      "15 검증 세트 정확도: 0.9688\n",
+      "16 검증 세트 정확도: 0.9694\n",
+      "17 검증 세트 정확도: 0.97\n",
+      "18 검증 세트 정확도: 0.9684\n",
+      "19 검증 세트 정확도: 0.9672\n"
      ]
     }
    ],
@@ -1959,7 +1949,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2004,7 +1994,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -2012,26 +2002,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.9026\n",
-      "1 테스트 정확도: 0.9307\n",
-      "2 테스트 정확도: 0.9394\n",
-      "3 테스트 정확도: 0.943\n",
-      "4 테스트 정확도: 0.9482\n",
-      "5 테스트 정확도: 0.951\n",
-      "6 테스트 정확도: 0.9514\n",
-      "7 테스트 정확도: 0.9539\n",
-      "8 테스트 정확도: 0.9545\n",
-      "9 테스트 정확도: 0.9569\n",
-      "10 테스트 정확도: 0.9597\n",
-      "11 테스트 정확도: 0.9599\n",
-      "12 테스트 정확도: 0.9604\n",
-      "13 테스트 정확도: 0.962\n",
-      "14 테스트 정확도: 0.9619\n",
-      "15 테스트 정확도: 0.9634\n",
-      "16 테스트 정확도: 0.963\n",
-      "17 테스트 정확도: 0.9647\n",
-      "18 테스트 정확도: 0.9653\n",
-      "19 테스트 정확도: 0.9659\n"
+      "0 검증 세트 정확도: 0.9018\n",
+      "1 검증 세트 정확도: 0.9334\n",
+      "2 검증 세트 정확도: 0.943\n",
+      "3 검증 세트 정확도: 0.947\n",
+      "4 검증 세트 정확도: 0.952\n",
+      "5 검증 세트 정확도: 0.953\n",
+      "6 검증 세트 정확도: 0.9558\n",
+      "7 검증 세트 정확도: 0.959\n",
+      "8 검증 세트 정확도: 0.9586\n",
+      "9 검증 세트 정확도: 0.961\n",
+      "10 검증 세트 정확도: 0.9624\n",
+      "11 검증 세트 정확도: 0.9622\n",
+      "12 검증 세트 정확도: 0.9638\n",
+      "13 검증 세트 정확도: 0.9666\n",
+      "14 검증 세트 정확도: 0.9662\n",
+      "15 검증 세트 정확도: 0.9662\n",
+      "16 검증 세트 정확도: 0.967\n",
+      "17 검증 세트 정확도: 0.9676\n",
+      "18 검증 세트 정확도: 0.9682\n",
+      "19 검증 세트 정확도: 0.9674\n"
      ]
     }
    ],
@@ -2072,7 +2062,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2084,7 +2074,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
@@ -2127,7 +2117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -2181,7 +2171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
@@ -2191,7 +2181,7 @@
        " <tf.Variable 'hidden1/bias:0' shape=(3,) dtype=float32_ref>]"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 67,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2209,7 +2199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [
     {
@@ -2218,7 +2208,7 @@
        "<tf.Tensor 'hidden1/kernel:0' shape=(2, 3) dtype=float32_ref>"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 68,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2229,7 +2219,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
@@ -2238,7 +2228,7 @@
        "<tf.Tensor 'hidden1/bias:0' shape=(3,) dtype=float32_ref>"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 69,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2256,7 +2246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2290,7 +2280,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2303,7 +2293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2313,7 +2303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
@@ -2321,26 +2311,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.8987\n",
-      "1 테스트 정확도: 0.931\n",
-      "2 테스트 정확도: 0.9371\n",
-      "3 테스트 정확도: 0.9418\n",
-      "4 테스트 정확도: 0.9437\n",
-      "5 테스트 정확도: 0.9477\n",
-      "6 테스트 정확도: 0.9494\n",
-      "7 테스트 정확도: 0.9524\n",
-      "8 테스트 정확도: 0.9513\n",
-      "9 테스트 정확도: 0.9522\n",
-      "10 테스트 정확도: 0.9536\n",
-      "11 테스트 정확도: 0.9538\n",
-      "12 테스트 정확도: 0.9536\n",
-      "13 테스트 정확도: 0.9548\n",
-      "14 테스트 정확도: 0.9537\n",
-      "15 테스트 정확도: 0.9552\n",
-      "16 테스트 정확도: 0.9552\n",
-      "17 테스트 정확도: 0.9551\n",
-      "18 테스트 정확도: 0.9552\n",
-      "19 테스트 정확도: 0.9554\n"
+      "0 검증 세트 정확도: 0.8962\n",
+      "1 검증 세트 정확도: 0.9296\n",
+      "2 검증 세트 정확도: 0.94\n",
+      "3 검증 세트 정확도: 0.9436\n",
+      "4 검증 세트 정확도: 0.9484\n",
+      "5 검증 세트 정확도: 0.9506\n",
+      "6 검증 세트 정확도: 0.9506\n",
+      "7 검증 세트 정확도: 0.9536\n",
+      "8 검증 세트 정확도: 0.9554\n",
+      "9 검증 세트 정확도: 0.9568\n",
+      "10 검증 세트 정확도: 0.9564\n",
+      "11 검증 세트 정확도: 0.9566\n",
+      "12 검증 세트 정확도: 0.957\n",
+      "13 검증 세트 정확도: 0.9578\n",
+      "14 검증 세트 정확도: 0.9592\n",
+      "15 검증 세트 정확도: 0.9574\n",
+      "16 검증 세트 정확도: 0.9576\n",
+      "17 검증 세트 정확도: 0.96\n",
+      "18 검증 세트 정확도: 0.959\n",
+      "19 검증 세트 정확도: 0.9604\n"
      ]
     }
    ],
@@ -2367,7 +2357,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2386,7 +2376,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2405,7 +2395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 76,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2431,7 +2421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
@@ -2439,26 +2429,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.9035\n",
-      "1 테스트 정확도: 0.932\n",
-      "2 테스트 정확도: 0.9398\n",
-      "3 테스트 정확도: 0.9435\n",
-      "4 테스트 정확도: 0.9471\n",
-      "5 테스트 정확도: 0.949\n",
-      "6 테스트 정확도: 0.9499\n",
-      "7 테스트 정확도: 0.9492\n",
-      "8 테스트 정확도: 0.9518\n",
-      "9 테스트 정확도: 0.9521\n",
-      "10 테스트 정확도: 0.9529\n",
-      "11 테스트 정확도: 0.9536\n",
-      "12 테스트 정확도: 0.953\n",
-      "13 테스트 정확도: 0.9535\n",
-      "14 테스트 정확도: 0.9525\n",
-      "15 테스트 정확도: 0.9538\n",
-      "16 테스트 정확도: 0.953\n",
-      "17 테스트 정확도: 0.9551\n",
-      "18 테스트 정확도: 0.9549\n",
-      "19 테스트 정확도: 0.9555\n"
+      "0 검증 세트 정확도: 0.902\n",
+      "1 검증 세트 정확도: 0.9308\n",
+      "2 검증 세트 정확도: 0.9432\n",
+      "3 검증 세트 정확도: 0.9474\n",
+      "4 검증 세트 정확도: 0.9514\n",
+      "5 검증 세트 정확도: 0.9524\n",
+      "6 검증 세트 정확도: 0.9524\n",
+      "7 검증 세트 정확도: 0.9558\n",
+      "8 검증 세트 정확도: 0.9554\n",
+      "9 검증 세트 정확도: 0.9562\n",
+      "10 검증 세트 정확도: 0.9568\n",
+      "11 검증 세트 정확도: 0.955\n",
+      "12 검증 세트 정확도: 0.9574\n",
+      "13 검증 세트 정확도: 0.9578\n",
+      "14 검증 세트 정확도: 0.9578\n",
+      "15 검증 세트 정확도: 0.9572\n",
+      "16 검증 세트 정확도: 0.9566\n",
+      "17 검증 세트 정확도: 0.9576\n",
+      "18 검증 세트 정확도: 0.9592\n",
+      "19 검증 세트 정확도: 0.958\n"
      ]
     }
    ],
@@ -2492,7 +2482,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2535,7 +2525,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2549,7 +2539,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 80,
    "metadata": {},
    "outputs": [
     {
@@ -2557,26 +2547,26 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Restoring parameters from ./my_model_final.ckpt\n",
-      "0 테스트 정확도: 0.9021\n",
-      "1 테스트 정확도: 0.9319\n",
-      "2 테스트 정확도: 0.9425\n",
-      "3 테스트 정확도: 0.945\n",
-      "4 테스트 정확도: 0.9473\n",
-      "5 테스트 정확도: 0.9481\n",
-      "6 테스트 정확도: 0.951\n",
-      "7 테스트 정확도: 0.9507\n",
-      "8 테스트 정확도: 0.9515\n",
-      "9 테스트 정확도: 0.9524\n",
-      "10 테스트 정확도: 0.9513\n",
-      "11 테스트 정확도: 0.9523\n",
-      "12 테스트 정확도: 0.9522\n",
-      "13 테스트 정확도: 0.954\n",
-      "14 테스트 정확도: 0.9539\n",
-      "15 테스트 정확도: 0.9537\n",
-      "16 테스트 정확도: 0.9547\n",
-      "17 테스트 정확도: 0.954\n",
-      "18 테스트 정확도: 0.9538\n",
-      "19 테스트 정확도: 0.9547\n"
+      "0 검증 세트 정확도: 0.902\n",
+      "1 검증 세트 정확도: 0.9308\n",
+      "2 검증 세트 정확도: 0.9432\n",
+      "3 검증 세트 정확도: 0.9474\n",
+      "4 검증 세트 정확도: 0.9514\n",
+      "5 검증 세트 정확도: 0.9524\n",
+      "6 검증 세트 정확도: 0.9524\n",
+      "7 검증 세트 정확도: 0.9558\n",
+      "8 검증 세트 정확도: 0.9554\n",
+      "9 검증 세트 정확도: 0.9562\n",
+      "10 검증 세트 정확도: 0.9568\n",
+      "11 검증 세트 정확도: 0.955\n",
+      "12 검증 세트 정확도: 0.9574\n",
+      "13 검증 세트 정확도: 0.9578\n",
+      "14 검증 세트 정확도: 0.9578\n",
+      "15 검증 세트 정확도: 0.9572\n",
+      "16 검증 세트 정확도: 0.9566\n",
+      "17 검증 세트 정확도: 0.9576\n",
+      "18 검증 세트 정확도: 0.9592\n",
+      "19 검증 세트 정확도: 0.958\n"
      ]
     }
    ],
@@ -2622,7 +2612,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 81,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2639,7 +2629,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2656,7 +2646,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2672,7 +2662,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2689,7 +2679,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 85,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2705,7 +2695,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 86,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2735,7 +2725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 87,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2752,7 +2742,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 88,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2762,18 +2752,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 89,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.9579\n",
-      "1 테스트 정확도: 0.9708\n",
-      "2 테스트 정확도: 0.9731\n",
-      "3 테스트 정확도: 0.9793\n",
-      "4 테스트 정확도: 0.9798\n"
+      "0 검증 세트 정확도: 0.9566\n",
+      "1 검증 세트 정확도: 0.9722\n",
+      "2 검증 세트 정확도: 0.9764\n",
+      "3 검증 세트 정확도: 0.9814\n",
+      "4 검증 세트 정확도: 0.9836\n"
      ]
     }
    ],
@@ -2815,7 +2805,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 90,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2842,7 +2832,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2868,7 +2858,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 92,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2888,7 +2878,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 93,
    "metadata": {
     "scrolled": true
    },
@@ -2897,26 +2887,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.8343\n",
-      "1 테스트 정확도: 0.8726\n",
-      "2 테스트 정확도: 0.8832\n",
-      "3 테스트 정확도: 0.8899\n",
-      "4 테스트 정확도: 0.8959\n",
-      "5 테스트 정확도: 0.8986\n",
-      "6 테스트 정확도: 0.9011\n",
-      "7 테스트 정확도: 0.9032\n",
-      "8 테스트 정확도: 0.9046\n",
-      "9 테스트 정확도: 0.9047\n",
-      "10 테스트 정확도: 0.9065\n",
-      "11 테스트 정확도: 0.9059\n",
-      "12 테스트 정확도: 0.9072\n",
-      "13 테스트 정확도: 0.9072\n",
-      "14 테스트 정확도: 0.9069\n",
-      "15 테스트 정확도: 0.9071\n",
-      "16 테스트 정확도: 0.9064\n",
-      "17 테스트 정확도: 0.9071\n",
-      "18 테스트 정확도: 0.9068\n",
-      "19 테스트 정확도: 0.9063\n"
+      "0 검증 세트 정확도: 0.831\n",
+      "1 검증 세트 정확도: 0.871\n",
+      "2 검증 세트 정확도: 0.8838\n",
+      "3 검증 세트 정확도: 0.8934\n",
+      "4 검증 세트 정확도: 0.8966\n",
+      "5 검증 세트 정확도: 0.8988\n",
+      "6 검증 세트 정확도: 0.9016\n",
+      "7 검증 세트 정확도: 0.9044\n",
+      "8 검증 세트 정확도: 0.9058\n",
+      "9 검증 세트 정확도: 0.906\n",
+      "10 검증 세트 정확도: 0.9068\n",
+      "11 검증 세트 정확도: 0.9054\n",
+      "12 검증 세트 정확도: 0.907\n",
+      "13 검증 세트 정확도: 0.9084\n",
+      "14 검증 세트 정확도: 0.9088\n",
+      "15 검증 세트 정확도: 0.9064\n",
+      "16 검증 세트 정확도: 0.9066\n",
+      "17 검증 세트 정확도: 0.9066\n",
+      "18 검증 세트 정확도: 0.9066\n",
+      "19 검증 세트 정확도: 0.9052\n"
      ]
     }
    ],
@@ -2944,7 +2934,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2968,7 +2958,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 95,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2977,7 +2967,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 96,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3001,7 +2991,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 97,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3022,7 +3012,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 98,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3042,7 +3032,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 99,
    "metadata": {
     "scrolled": true
    },
@@ -3051,26 +3041,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.8299\n",
-      "1 테스트 정확도: 0.8778\n",
-      "2 테스트 정확도: 0.8915\n",
-      "3 테스트 정확도: 0.9016\n",
-      "4 테스트 정확도: 0.9068\n",
-      "5 테스트 정확도: 0.9103\n",
-      "6 테스트 정확도: 0.9124\n",
-      "7 테스트 정확도: 0.9137\n",
-      "8 테스트 정확도: 0.9149\n",
-      "9 테스트 정확도: 0.9175\n",
-      "10 테스트 정확도: 0.9176\n",
-      "11 테스트 정확도: 0.9184\n",
-      "12 테스트 정확도: 0.9191\n",
-      "13 테스트 정확도: 0.9182\n",
-      "14 테스트 정확도: 0.9195\n",
-      "15 테스트 정확도: 0.9201\n",
-      "16 테스트 정확도: 0.918\n",
-      "17 테스트 정확도: 0.9184\n",
-      "18 테스트 정확도: 0.9181\n",
-      "19 테스트 정확도: 0.9174\n"
+      "0 검증 세트 정확도: 0.8274\n",
+      "1 검증 세트 정확도: 0.8766\n",
+      "2 검증 세트 정확도: 0.8952\n",
+      "3 검증 세트 정확도: 0.9016\n",
+      "4 검증 세트 정확도: 0.908\n",
+      "5 검증 세트 정확도: 0.9096\n",
+      "6 검증 세트 정확도: 0.9124\n",
+      "7 검증 세트 정확도: 0.9154\n",
+      "8 검증 세트 정확도: 0.9178\n",
+      "9 검증 세트 정확도: 0.919\n",
+      "10 검증 세트 정확도: 0.92\n",
+      "11 검증 세트 정확도: 0.9224\n",
+      "12 검증 세트 정확도: 0.9212\n",
+      "13 검증 세트 정확도: 0.9228\n",
+      "14 검증 세트 정확도: 0.9224\n",
+      "15 검증 세트 정확도: 0.9216\n",
+      "16 검증 세트 정확도: 0.9218\n",
+      "17 검증 세트 정확도: 0.9228\n",
+      "18 검증 세트 정확도: 0.9216\n",
+      "19 검증 세트 정확도: 0.9214\n"
      ]
     }
    ],
@@ -3098,7 +3088,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3110,7 +3100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 101,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3131,7 +3121,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 102,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3153,7 +3143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 103,
    "metadata": {
     "scrolled": true
    },
@@ -3162,26 +3152,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.9205\n",
-      "1 테스트 정확도: 0.942\n",
-      "2 테스트 정확도: 0.9469\n",
-      "3 테스트 정확도: 0.9511\n",
-      "4 테스트 정확도: 0.9542\n",
-      "5 테스트 정확도: 0.9569\n",
-      "6 테스트 정확도: 0.961\n",
-      "7 테스트 정확도: 0.9598\n",
-      "8 테스트 정확도: 0.9612\n",
-      "9 테스트 정확도: 0.9656\n",
-      "10 테스트 정확도: 0.9662\n",
-      "11 테스트 정확도: 0.9616\n",
-      "12 테스트 정확도: 0.9663\n",
-      "13 테스트 정확도: 0.9668\n",
-      "14 테스트 정확도: 0.965\n",
-      "15 테스트 정확도: 0.9678\n",
-      "16 테스트 정확도: 0.9696\n",
-      "17 테스트 정확도: 0.9674\n",
-      "18 테스트 정확도: 0.9694\n",
-      "19 테스트 정확도: 0.9683\n"
+      "0 검증 세트 정확도: 0.9238\n",
+      "1 검증 세트 정확도: 0.943\n",
+      "2 검증 세트 정확도: 0.9508\n",
+      "3 검증 세트 정확도: 0.9586\n",
+      "4 검증 세트 정확도: 0.9624\n",
+      "5 검증 세트 정확도: 0.9608\n",
+      "6 검증 세트 정확도: 0.963\n",
+      "7 검증 세트 정확도: 0.968\n",
+      "8 검증 세트 정확도: 0.9676\n",
+      "9 검증 세트 정확도: 0.9706\n",
+      "10 검증 세트 정확도: 0.9694\n",
+      "11 검증 세트 정확도: 0.969\n",
+      "12 검증 세트 정확도: 0.9696\n",
+      "13 검증 세트 정확도: 0.9694\n",
+      "14 검증 세트 정확도: 0.9716\n",
+      "15 검증 세트 정확도: 0.9716\n",
+      "16 검증 세트 정확도: 0.9722\n",
+      "17 검증 세트 정확도: 0.971\n",
+      "18 검증 세트 정확도: 0.9724\n",
+      "19 검증 세트 정확도: 0.973\n"
      ]
     }
    ],
@@ -3216,7 +3206,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3260,7 +3250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 105,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3279,7 +3269,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 106,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3297,7 +3287,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 107,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3314,7 +3304,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 108,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3324,33 +3314,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.9512\n",
-      "1 테스트 정확도: 0.9671\n",
-      "2 테스트 정확도: 0.972\n",
-      "3 테스트 정확도: 0.9757\n",
-      "4 테스트 정확도: 0.975\n",
-      "5 테스트 정확도: 0.9757\n",
-      "6 테스트 정확도: 0.9777\n",
-      "7 테스트 정확도: 0.9796\n",
-      "8 테스트 정확도: 0.9806\n",
-      "9 테스트 정확도: 0.9798\n",
-      "10 테스트 정확도: 0.9813\n",
-      "11 테스트 정확도: 0.9809\n",
-      "12 테스트 정확도: 0.9817\n",
-      "13 테스트 정확도: 0.9804\n",
-      "14 테스트 정확도: 0.9819\n",
-      "15 테스트 정확도: 0.9823\n",
-      "16 테스트 정확도: 0.9833\n",
-      "17 테스트 정확도: 0.9827\n",
-      "18 테스트 정확도: 0.9825\n",
-      "19 테스트 정확도: 0.9822\n"
+      "0 검증 세트 정확도: 0.9568\n",
+      "1 검증 세트 정확도: 0.9696\n",
+      "2 검증 세트 정확도: 0.9714\n",
+      "3 검증 세트 정확도: 0.9776\n",
+      "4 검증 세트 정확도: 0.9766\n",
+      "5 검증 세트 정확도: 0.978\n",
+      "6 검증 세트 정확도: 0.9818\n",
+      "7 검증 세트 정확도: 0.9814\n",
+      "8 검증 세트 정확도: 0.9802\n",
+      "9 검증 세트 정확도: 0.9822\n",
+      "10 검증 세트 정확도: 0.9814\n",
+      "11 검증 세트 정확도: 0.9844\n",
+      "12 검증 세트 정확도: 0.9814\n",
+      "13 검증 세트 정확도: 0.9832\n",
+      "14 검증 세트 정확도: 0.9848\n",
+      "15 검증 세트 정확도: 0.9846\n",
+      "16 검증 세트 정확도: 0.9842\n",
+      "17 검증 세트 정확도: 0.9846\n",
+      "18 검증 세트 정확도: 0.9844\n",
+      "19 검증 세트 정확도: 0.9846\n"
      ]
     }
    ],
@@ -3377,7 +3367,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 110,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3400,7 +3390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3420,7 +3410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 112,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3436,7 +3426,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 113,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3465,7 +3455,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 114,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3475,7 +3465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 115,
    "metadata": {
     "scrolled": false
    },
@@ -3484,26 +3474,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 테스트 정확도: 0.954\n",
-      "1 테스트 정확도: 0.9657\n",
-      "2 테스트 정확도: 0.9707\n",
-      "3 테스트 정확도: 0.9743\n",
-      "4 테스트 정확도: 0.9761\n",
-      "5 테스트 정확도: 0.9777\n",
-      "6 테스트 정확도: 0.9775\n",
-      "7 테스트 정확도: 0.979\n",
-      "8 테스트 정확도: 0.9769\n",
-      "9 테스트 정확도: 0.9803\n",
-      "10 테스트 정확도: 0.9803\n",
-      "11 테스트 정확도: 0.9798\n",
-      "12 테스트 정확도: 0.9818\n",
-      "13 테스트 정확도: 0.9813\n",
-      "14 테스트 정확도: 0.9811\n",
-      "15 테스트 정확도: 0.9806\n",
-      "16 테스트 정확도: 0.9812\n",
-      "17 테스트 정확도: 0.9819\n",
-      "18 테스트 정확도: 0.9822\n",
-      "19 테스트 정확도: 0.982\n"
+      "0 검증 세트 정확도: 0.9556\n",
+      "1 검증 세트 정확도: 0.9702\n",
+      "2 검증 세트 정확도: 0.9694\n",
+      "3 검증 세트 정확도: 0.973\n",
+      "4 검증 세트 정확도: 0.9768\n",
+      "5 검증 세트 정확도: 0.9762\n",
+      "6 검증 세트 정확도: 0.9798\n",
+      "7 검증 세트 정확도: 0.9812\n",
+      "8 검증 세트 정확도: 0.9836\n",
+      "9 검증 세트 정확도: 0.9816\n",
+      "10 검증 세트 정확도: 0.9824\n",
+      "11 검증 세트 정확도: 0.9836\n",
+      "12 검증 세트 정확도: 0.9816\n",
+      "13 검증 세트 정확도: 0.983\n",
+      "14 검증 세트 정확도: 0.9832\n",
+      "15 검증 세트 정확도: 0.9842\n",
+      "16 검증 세트 정확도: 0.9838\n",
+      "17 검증 세트 정확도: 0.9838\n",
+      "18 검증 세트 정확도: 0.984\n",
+      "19 검증 세트 정확도: 0.985\n"
      ]
     }
    ],