- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 11 - 20 of 28 for ' (0.03 sec)
-
grid_search.rst.txt
= [ {'C': [1, 10, 100, 1000], 'kernel': ['linear']}, {'C': [1,...e=.1), 'kernel': ['rbf'], 'class_weight':['balanced', None]}...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
glossary.rst.txt
of ['no', 'yes'], 'yes' is the positive class; of ['no', 'YES'],...... param_grid={'loss': ['log_loss', 'hinge']}) This means that...scikit-learn.org/stable/_sources/glossary.rst.txt -
getting_started.rst.txt
param_distributions = {'n_estimators': randint(1, 5), ... 'max_depth': randint(5,...param_distributions={'max_depth': ..., 'n_estimators': ...}, random_state=0)...scikit-learn.org/stable/_sources/getting_started.rst.txt -
testimonials.rst.txt
I think it's the most well-designed ML package I've seen so far....in the lead's tenure on our site. Also, our users' profiles consist...scikit-learn.org/stable/_sources/testimonials/testimonials.rst.txt -
decomposition.rst.txt
Descent ('cd') [5]_, and Multiplicative Update ('mu') [6]_. The...optional parameter ``svd_solver='randomized'`` is very useful in that...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
faq.rst.txt
need to specify algorithm='brute' as the default assumes >>>...eps=5, min_samples=2, algorithm='brute') # doctest: +SKIP (array([0,...scikit-learn.org/stable/_sources/faq.rst.txt -
clustering.rst.txt
Their 'sqrt' and 'sum' averages are the geometric...s(i, k) - max [ a(i, k') + s(i, k') \forall k' \neq k ] Where :math:`s(i,...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
plot_release_highlights_1_4_0.rst.txt
type: <class 'polars.dataframe.frame.DataFrame'> .. GENERATED...`set_output` ---------- scikit-learn's transformers now support polars...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_4_0.r... -
roadmap.rst.txt
right now it's impossible to clone a `CalibratedClassifier`...scikit-learn.org/stable/_sources/roadmap.rst.txt -
feature_extraction.rst.txt
() array([' w', 'ds', 'or', 'pr', 'rd', 's ', 'wo', 'wp'], ...)...array(['and', 'document', 'first', 'is', 'one', 'second', 'the',...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt