Sorry, I meant https://github.com/scikit-learn/scikit-learn/issues/4301
On 18 May 2015 at 12:10, Joel Nothman wrote:
> Sorry, grid search (and similar) does not support clusterers. This
> probably should be formally tracked as an issue.
> https://github.com/scikit-learn/scikit-learn/issues/4040
Sorry, grid search (and similar) does not support clusterers. This probably
should be formally tracked as an issue.
https://github.com/scikit-learn/scikit-learn/issues/4040 might be helpful
to you.
On 18 May 2015 at 11:56, Jitesh Khandelwal wrote:
> I have recently been using grid search to eval
I have recently been using grid search to evaluate a custom method for
dimensionality reduction (DR) along with supervised and unsupervised
estimators later in the pipeline to discover its usefulness.
gr = grid_search.GridSearchCV(
pipeline
, param_grid, cv = None)
The scoring functions I used
Hi Sam,
I think this could be interesting. You could allow for learning parameters
on each sub-cluster by accepting a transformer as a parameter, then using
sample = sklearn.base.clone(transformer).fit_transform(sample).
I suspect bisecting k-means is notable enough and different enough for
inclu
Hi Andy,
I'm following up on this from a while ago, because I finally got around to
trying to implement it.
To get the minority f1 score from my grid search, I have:
min_f_scorer = make_scorer(f1_score(pos_label=1))
grid_search = GridSearchCV(pipeline, parameters, verbose=1, cv=3,
scoring=min_f1_
