Updated to use fstrings

ntn23 · Nov 8, 2020 · b39a8ff · b39a8ff
1 parent 534a518
commit b39a8ff
Showing 1 changed file with 4 additions and 4 deletions.
diff --git a/ipython/python35/Lecture_TextMining_3.ipynb b/ipython/python35/Lecture_TextMining_3.ipynb
@@ -526,7 +526,7 @@
     "model = LogisticRegression()\n",
     "model.fit(X_train_binary, Y_train)\n",
     "\n",
-    "print(\"Area under the ROC curve on the test data = %.3f\" % metrics.roc_auc_score(model.predict(X_test_binary), Y_test))"
+    "print(f'Area under the ROC curve on the test data = {round(metrics.roc_auc_score(model.predict(X_test_binary), Y_test), 3)}')"
    ]
   },
   {
@@ -605,7 +605,7 @@
     "model = LogisticRegression()\n",
     "model.fit(X_train_counts, Y_train)\n",
     "\n",
-    "print(\"Area under the ROC curve on the test data = %.3f\" % metrics.roc_auc_score(model.predict(X_test_counts), Y_test))"
+    "print(f'Area under the ROC curve on the test data = {round(metrics.roc_auc_score(model.predict(X_test_counts), Y_test), 3)}')"
    ]
   },
   {
@@ -684,7 +684,7 @@
     "model = LogisticRegression()\n",
     "model.fit(X_train_tfidf, Y_train)\n",
     "\n",
-    "print(\"Area under the ROC curve on the test data = %.3f\" % metrics.roc_auc_score(model.predict(X_test_counts), Y_test))"
+    "print(f'Area under the ROC curve on the test data = {round(metrics.roc_auc_score(model.predict(X_test_counts), Y_test), 3)}')"
    ]
   },
   {
@@ -829,7 +829,7 @@
     }
    ],
    "source": [
-    "print(\"AUC on the count data = %.3f\" % metrics.roc_auc_score(model.predict(X_test_tfidf), Y_test))"
+    "print(f'AUC on the count data = {round(metrics.roc_auc_score(model.predict(X_test_tfidf), Y_test), 3)}')"
    ]
   },
   {