assignments:assignment3
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assignments:assignment3 [2013/10/04 21:06] asa |
assignments:assignment3 [2013/10/04 21:08] asa [Part 3: Using the SVM] |
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| In this question we will consider both the Gaussian and polynomial kernels: | In this question we will consider both the Gaussian and polynomial kernels: | ||
| $$ | $$ | ||
| - | K_{gaus}(\mathbf{x}, \mathbf{x'} = \exp(-\gamma || \mathbf{x} - \mathbf{x}' ||^2) | + | K_{gaus}(\mathbf{x}, \mathbf{x'}) = \exp(-\gamma || \mathbf{x} - \mathbf{x}' ||^2) |
| $$ | $$ | ||
| $$ | $$ | ||
| - | K_{poly}(\mathbf{x}, \mathbf{x'} = (1 + \mathbf{x}^T \mathbf{x}') ^{p} | + | K_{poly}(\mathbf{x}, \mathbf{x'}) = (1 + \mathbf{x}^T \mathbf{x}') ^{p} |
| $$ | $$ | ||
| Plot the accuracy of the classifier, measured using the success rate and the area under the ROC curve | Plot the accuracy of the classifier, measured using the success rate and the area under the ROC curve | ||
| Line 79: | Line 79: | ||
| accomplished in PyML by: | accomplished in PyML by: | ||
| <code python> | <code python> | ||
| - | data.normalize() | + | >>> data.normalize() |
| </code> | </code> | ||
| Compare the results under this normalization with what you obtain | Compare the results under this normalization with what you obtain | ||
assignments/assignment3.txt ยท Last modified: 2016/09/20 09:34 by asa
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