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assignments:assignment1 [2016/08/31 19:04]
asa [Part 2: The nearest centroid classifier]
assignments:assignment1 [2016/08/31 19:07]
asa [Part 2: The nearest centroid classifier]
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 Show that for a binary classification problem where the number of positive examples equals the number of negative examples the nearest centroid classifier can be expressed as a linear classifier with the weight vector ​ Show that for a binary classification problem where the number of positive examples equals the number of negative examples the nearest centroid classifier can be expressed as a linear classifier with the weight vector ​
 $$\mathbf{w} = \frac{1}{N}\sum_{i=1}^N y_i \mathbf{x}_i.$$ $$\mathbf{w} = \frac{1}{N}\sum_{i=1}^N y_i \mathbf{x}_i.$$
-Hint:  consider the vector that connects the centroids of the two classes and draw a figure in two dimensions to help you think about the problem. ​ Also note that this form only holds if the two classes have equal number of examples.+Hint:  consider the vector that connects the centroids of the two classes and draw a figure in two dimensions to help you think about the problem. ​ Also note that this form only holds if the two classes have equal number of examples, so we'll assume that is the case.
  
 ===== Part 3:  Are my features useful? ===== ===== Part 3:  Are my features useful? =====
assignments/assignment1.txt ยท Last modified: 2016/08/31 19:07 by asa