Sorry, docstring is also a bit funny. Is the problem it is trying to solve have an __equality__ constraint for y_min, y_max or __inequality__ constraint for y_min / y_max?
Either way the produced solution does not satisfy such a constraint... On Tue, Jun 21, 2016 at 7:19 PM, Jonathan Taylor < jonathan.tay...@stanford.edu> wrote: > Should have included: > > In [*22*]: iso > > Out[*22*]: <module 'sklearn.isotonic' from > '/Users/jonathantaylor/anaconda/envs/py27/lib/python2.7/site-packages/sklearn/isotonic.pyc'> > > On Tue, Jun 21, 2016 at 7:18 PM, Jonathan Taylor < > jonathan.tay...@stanford.edu> wrote: > >> Was trying to fit isotonic regression with non-trivial y_min and y_max: >> >> In [*17*]: X >> >> Out[*17*]: >> >> array([ 1.26336413, 1.31853693, -0.57200917, 0.3072928 , -0.70686507, >> >> -0.17614937, -1.59943059, 1.05908504, 1.3958263 , 1.90580318, >> >> 0.20992272, 0.02836316, -0.08092235, 0.44438247, 0.01791253, >> >> -0.3771914 , -0.89577538, -0.37726249, -1.32687569, 0.18013201]) >> >> >> In [*18*]: iso.isotonic_regression(X, y_min=0, y_max=0.1) >> >> Out[*18*]: >> >> array([-0.00826919, -0.00826919, -0.00826919, -0.00826919, -0.00826919, >> >> -0.00826919, -0.00826919, 0.10449344, 0.10449344, 0.10449344, >> >> 0.10449344, 0.10449344, 0.10449344, 0.10449344, 0.10449344, >> >> 0.10449344, 0.10449344, 0.10449344, 0.10449344, 0.10449344]) >> >> >> The solution does not satisfy the bounds that each entry should be in >> [0,0.1] >> >> >> >> -- >> Jonathan Taylor >> Dept. of Statistics >> Sequoia Hall, 137 >> 390 Serra Mall >> Stanford, CA 94305 >> Tel: 650.723.9230 >> Fax: 650.725.8977 >> Web: http://www-stat.stanford.edu/~jtaylo >> > > > > -- > Jonathan Taylor > Dept. of Statistics > Sequoia Hall, 137 > 390 Serra Mall > Stanford, CA 94305 > Tel: 650.723.9230 > Fax: 650.725.8977 > Web: http://www-stat.stanford.edu/~jtaylo > -- Jonathan Taylor Dept. of Statistics Sequoia Hall, 137 390 Serra Mall Stanford, CA 94305 Tel: 650.723.9230 Fax: 650.725.8977 Web: http://www-stat.stanford.edu/~jtaylo
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