cs501r_f2016:lab2
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| You should also test different step sizes. Wikipedia doesn't discuss how to do this, but it should be straightforward for you to figure out; the algorithm description in the lecture notes includes the step size. (But try to figure it out: consider the update equation for a weight, and ask yourself: where should I put a stepsize parameter, to be able to adjust the magnitude of the weight update?) | You should also test different step sizes. Wikipedia doesn't discuss how to do this, but it should be straightforward for you to figure out; the algorithm description in the lecture notes includes the step size. (But try to figure it out: consider the update equation for a weight, and ask yourself: where should I put a stepsize parameter, to be able to adjust the magnitude of the weight update?) | ||
| - | For the Iris dataset, you should test ''c=1'', ''c=0.1'', ''c=0.01''. | + | For the Iris dataset, you should test at least ''c=1'', ''c=0.1'', ''c=0.01''. |
| - | For the CIFAR-10 dataset, you should test ''c=0.001'', ''c=0.00001''. | + | For the CIFAR-10 dataset, you should test at least ''c=0.001'', ''c=0.00001''. |
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| <code python> | <code python> | ||
| import matplotlib.pyplot as plt | import matplotlib.pyplot as plt | ||
| - | <code> | + | </code> |
| To create a new figure, call ''plt.figure''. To plot a line, call ''plt.plot''. Note that if you pass a matrix into ''plt.plot'', it will plot multiple lines at once, each with a different color; each column will generate a new line. | To create a new figure, call ''plt.figure''. To plot a line, call ''plt.plot''. Note that if you pass a matrix into ''plt.plot'', it will plot multiple lines at once, each with a different color; each column will generate a new line. | ||
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| Don't forget to label your axes! | Don't forget to label your axes! | ||
| + | |||
| + | You may find [[http://matplotlib.org/users/pyplot_tutorial.html|this tutorial on pyplot]] helpful. | ||
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cs501r_f2016/lab2.txt ยท Last modified: 2021/06/30 23:42 (external edit)
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