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linear_model.rst.txt
for example `cv=10` for 10-fold cross-validation, rather...computation 15.7 (2003): 1691-1714. <10.1162/089976603321891864>` |details-end|...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
grid_search.rst.txt
10, 100, 1000], 'kernel': ['linear']}, {'C': [1, 10, 100,...{'max_depth': [3, 5, 10], ... 'min_samples_split': [2, 5, 10]} >>> base_estimator...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
feature_extraction.rst.txt
For instance a collection of 10,000 short text documents (such...HashingVectorizer(n_features=10) >>> hv.transform(corpus) <4x10...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
getting_started.rst.txt
-10]] >>> # scale data according...5), ... 'max_depth': randint(5, 10)} ... >>> # now create a searchCV...scikit-learn.org/stable/_sources/getting_started.rst.txt -
classes.rst.txt
make_hastie_10_2 datasets.make_low_rank_matrix...scikit-learn.org/stable/_sources/modules/classes.rst.txt -
preprocessing.rst.txt
asarray([["a"] * 20 + ["b"] * 10 + ["c"] * 10 + ["d"] * 10], dtype=object).T...ca.pdf>`_ Neural computation 10.5 (1998): 1299-1319. .. _pre...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
plot_release_highlights_1_4_0.rst.txt
sin(10 * np.pi * X[:, 0]) - noise rf_no_cst...e(7) groups = rng.randint(0, 10, size=n_samples) sample_weights...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_4_0.r... -
clustering.rst.txt
toward feature space analysis" <10.1109/34.1000236>` D. Comaniciu...multi-way spectral clustering"<10.1093/imaiai/iay008>` Anil Damle,...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
decomposition.rst.txt
number of components is less than 10 (strict) and the number of samples...<https://link.springer.com/article/10.1007%2FBF02289233>`_ H. F. Kaiser,...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
plot_kmeans_digits.rst.txt
code-block:: none # digits: 10; # samples: 1797; # features...linewidths=3, color="w", zorder=10, ) plt.title( "K-means clustering...scikit-learn.org/stable/_sources/auto_examples/cluster/plot_kmeans_digits.rst.txt