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.taylor@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.taylor@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