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cs401r_w2016:lab2 [2016/01/15 17:37] admin |
cs401r_w2016:lab2 [2021/06/30 23:42] (current) |
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| For this lab, you will turn in an ipython notebook that implements the "Bayesian Concept Learning" model from Chapter 3 of MLAPP. | For this lab, you will turn in an ipython notebook that implements the "Bayesian Concept Learning" model from Chapter 3 of MLAPP. | ||
| + | |||
| + | [[http://liftothers.org/courses/stat_ml/mlapp_ch3.pdf|Here is a PDF of the relevant chapter.]] | ||
| Your notebook should perform the following functions: | Your notebook should perform the following functions: | ||
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| When you display your prior, likelihood, and posterior, your figure should look something like the ones in the book; my version is shown here: | When you display your prior, likelihood, and posterior, your figure should look something like the ones in the book; my version is shown here: | ||
| - | {{:cs401r_w2016:lab2_bayesian_concepts.png?direct&800|}} | + | {{:cs401r_w2016:lab2_plp.JPG?direct&800|}} |
| Similarly, when you display the posterior predictive, your figure should look something like this: | Similarly, when you display the posterior predictive, your figure should look something like this: | ||
| - | {{:cs401r_w2016:lab2_pp.png?direct&800|}} | + | {{:cs401r_w2016:lab2_predpost.JPG?direct&800|}} |
| ---- | ---- | ||
| Line 50: | Line 52: | ||
| <code python> | <code python> | ||
| - | prior = numpy.ones(( len(concepts), 1 )) | + | prior = numpy.ones(len(concepts)) |
| prior[0] = 5 | prior[0] = 5 | ||
| prior[1] = 5 | prior[1] = 5 | ||
| - | prior[2] = 5 | + | prior[30] = .01 |
| - | prior[21] = 5 | + | prior[31] = .01 |
| prior = prior / numpy.sum(prior) | prior = prior / numpy.sum(prior) | ||
| </code> | </code> | ||
| Line 85: | Line 87: | ||
| ---- | ---- | ||
| ====Hints:==== | ====Hints:==== | ||
| - | |||
| - | When using an ipython notebook, it's nice to make your plots show up inline. To do this, add the following lines to the first cell of your notebook: | ||
| - | |||
| - | <code python> | ||
| - | |||
| - | # this tells seaborn and matplotlib to generate plots inline in the notebook | ||
| - | %matplotlib inline | ||
| - | |||
| - | # these two lines allow you to control the figure size | ||
| - | %pylab inline | ||
| - | pylab.rcParams['figure.figsize'] = (16.0, 8.0) | ||
| - | |||
| - | </code> | ||
| - | |||
| You may find the following functions useful: | You may find the following functions useful: | ||