assignments:assignment1

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assignments:assignment1 [2016/08/30 18:26] asa |
assignments:assignment1 [2016/08/31 19:04] 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. | + | 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. |

===== 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

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