<div>Thanks very much. I will try them in the next days.</div>
<div> </div>
<div> </div>
<div>Zonglei Zhen<br><br></div>
<div class="gmail_quote">On Fri, Aug 12, 2011 at 12:00 AM, Yaroslav Halchenko <span dir="ltr"><<a href="mailto:debian@onerussian.com">debian@onerussian.com</a>></span> wrote:<br>
<blockquote style="BORDER-LEFT: #ccc 1px solid; MARGIN: 0px 0px 0px 0.8ex; PADDING-LEFT: 1ex" class="gmail_quote">indeed we have no good tutorial/example for regressions yet besides one<br>for GPR<br><br>doc/examples/gpr.py<br>
<br>also we interface to SVR regressions (from libsvm and shogun) and started<br>to add interfaces to scikits.learn. Some samples of them are available from<br>regrswh, so on my system:<br><br>*In [5]: print '\n'.join([str(x) for x in regrswh[:]])<br>
<libsvm epsilon-SVR><br><libsvm nu-SVR><br><sg.LinSVMR()/libsvr><br><skl.PLSRegression_1d()><br><skl.LARS()><br><skl.LassoLARS()><br><GPR(kernel='linear')><br><GPR(kernel='sqexp')><br>
<br>As for "howto" -- just the same way you use classifiers -- then ConfusionMatrix<br>in .stats would be replaced with RegressionStatistics. e.g.<br><br>In [5]: from mvpa.suite import *<br><br>In [6]: from mvpa.testing.datasets import datasets as testing_datasets<br>
<br>In [7]: cve = CrossValidation(regrswh[:][0], NFoldPartitioner(), postproc=mean_sample(), errorfx=corr_error, enable_ca=['training_stats', 'stats'])<br><br>In [8]: print cve(testing_datasets['chirp_linear'])<br>
<Dataset: 1x1@float64, <sa: cvfolds>><br><br>In [9]: print cve.ca.stats<br>Statistics Mean Std Min Max<br>---------- ----- ----- ----- -----<br>Data:<br> RMP_t 0.668 0.015 0.639 0.681<br> STD_t 0.661 0.015 0.631 0.675<br>
RMP_p 0.644 0.043 0.593 0.731<br> STD_p 0.637 0.042 0.583 0.721<br>Results:<br> CCe 0.06 0.016 0.036 0.084<br> RMSE 0.232 0.027 0.184 0.266<br>RMSE/RMP_t 0.348 0.043 0.27 0.4<br>Summary:<br>
CCe 0.06 p= 3.65268e-137<br> RMSE 0.23<br>RMSE/RMP_t 0.35<br> # of sets 6<br>
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<div></div>
<div class="h5"><br><br>On Mon, 08 Aug 2011, Zhen Zonglei wrote:<br><br>> Hi Guys:<br><br><br><br>> I am trying to do multivariate regression analysis to predict<br>> subject-specific score with pymvpa 0.6. But, I did not find some<br>
> examples about this in the manual. What regressions are implemented in<br>> the toolbox? Could you please show me how to do regression analysis in<br>> the toolbox?<br><br><br>> Best<br><br><br>> Zonglei Zhen<br>
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Keep in touch <a href="http://www.onerussian.com/" target="_blank">www.onerussian.com</a><br>Yaroslav Halchenko <a href="http://www.ohloh.net/accounts/yarikoptic" target="_blank">www.ohloh.net/accounts/yarikoptic</a><br>
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