Hi,
I have a custom kernel function, and I am using GridSearchCV function with
SVC(kernel=my_kernel).
my_kernel function takes a parameter k to tune, so I was wondering whether it's
possible to configure param_grid option to tune the parameter of my custom
kernel function.
For example, it's possible to tune gamma parameter for RBF kernel as follows.
Can I provide a param_grid=dict(k=k_range) kind of option for my custom kernel?
gamma_range = 10. ** np.arange(-5, 4)
param_grid = dict(gamma=gamma_range)
grid = GridSearchCV(SVC(), param_grid=param_grid, cv=StratifiedKFold(y=Y,
k=5))
Thanks,
Ev
------------------------------------------------------------------------------
Open source business process management suite built on Java and Eclipse
Turn processes into business applications with Bonita BPM Community Edition
Quickly connect people, data, and systems into organized workflows
Winner of BOSSIE, CODIE, OW2 and Gartner awards
http://p.sf.net/sfu/Bonitasoft
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
