Update AdviceQuiz.md

myounus96 · Aug 7, 2017 · d476687 · d476687
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diff --git a/Stanford_Machine_Learning/Week6/AdviceQuiz.md b/Stanford_Machine_Learning/Week6/AdviceQuiz.md
@@ -31,13 +31,9 @@ Useful Info: Since the hypothesis performs <b> poorly </b> on the training set,
 True/False | Answer | Explanation
 --- | --- | ---
 True | Try adding polynomial features. | The poor performance on both the training and test sets suggests a high bias problem. Adding more complex features will increase the complexity of the hypothesis, thereby improving the fit to both the train and test data.
-False | Try increasing the regularization parameter λ. | The poor performance on both the training and test sets
-suggests a high bias problem. Increasing the regularization parameter will allow the hypothesis to fit the data worse,
-decreasing both training and test set performance.
-False | Try using a smaller set of features. | The poor performance on both the training and test sets
-suggests a high bias problem. Using fewer features will decrease the complexity of the hypothesis and will make the bias problem worse
-True | Try to obtain and use additional features. |  The poor performance on both the training and test sets suggests a high bias problem. Using additional features will increase the complexity of the hypothesis, thereby improving the
-fit to both the train and test data.
+False | Try increasing the regularization parameter λ. | The poor performance on both the training and test sets suggests a high bias problem. Increasing the regularization parameter will allow the hypothesis to fit the data worse, decreasing both training and test set performance.
+False | Try using a smaller set of features. | The poor performance on both the training and test sets suggests a high bias problem. Using fewer features will decrease the complexity of the hypothesis and will make the bias problem worse
+True | Try to obtain and use additional features. |  The poor performance on both the training and test sets suggests a high bias problem. Using additional features will increase the complexity of the hypothesis, thereby improving the fit to both the train and test data.
 
 Question 4
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