출력 메시지 번역, 노트북 재실행

notebooks/train_simple_model.ipynb

@@ -167,7 +167,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Training accuracy = 0.588, precision = 0.585, recall = 0.588, f1 = 0.584\n"
+      "훈련 정확도 = 0.588, 정밀도 = 0.585, 재현율 = 0.588, f1 = 0.584\n"
      ]
     }
    ],
@@ -177,7 +177,7 @@
     "y_train_pred = np.argmax(clf.oob_decision_function_,axis=1)\n",
     "\n",
     "accuracy, precision, recall, f1 = get_metrics(y_train, y_train_pred)\n",
-    "print(\"Training accuracy = %.3f, precision = %.3f, recall = %.3f, f1 = %.3f\" % (accuracy, precision, recall, f1))"
+    "print(\"훈련 정확도 = %.3f, 정밀도 = %.3f, 재현율 = %.3f, f1 = %.3f\" % (accuracy, precision, recall, f1))"
    ]
   },
   {
@@ -191,13 +191,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Validation accuracy = 0.611, precision = 0.612, recall = 0.611, f1 = 0.608\n"
+      "검증 정확도 = 0.611, 정밀도 = 0.612, 재현율 = 0.611, f1 = 0.608\n"
      ]
     }
    ],
    "source": [
     "accuracy, precision, recall, f1 = get_metrics(y_test, y_predicted)\n",
-    "print(\"Validation accuracy = %.3f, precision = %.3f, recall = %.3f, f1 = %.3f\" % (accuracy, precision, recall, f1))"
+    "print(\"검증 정확도 = %.3f, 정밀도 = %.3f, 재현율 = %.3f, f1 = %.3f\" % (accuracy, precision, recall, f1))"
    ]
   },
   {
@@ -248,7 +248,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.21 probability of the question receiving a high score according to our model\n"
+      "이 질문이 양성 샘플일 확률: 0.21\n"
      ]
     }
    ],
@@ -261,7 +261,7 @@
     "probs = get_model_probabilities_for_input_texts(test_q)\n",
     "\n",
     "# Index 1 corresponds to the positive class here\n",
-    "print(\"%s probability of the question receiving a high score according to our model\" % (probs[0][1]))"
+    "print(\"이 질문이 양성 샘플일 확률: %s\" % (probs[0][1]))"
    ]
   }
  ],