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Results 1 - 8 of 8 for pipe (0.08 sec)
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getting_started.rst.txt
create a pipeline object >>> pipe = make_pipeline( ... StandardScaler(),...# fit the whole pipeline >>> pipe.fit(X_train, y_train) Pipel...scikit-learn.org/stable/_sources/getting_started.rst.txt -
grid_search.rst.txt
tion import SelectKBest >>> pipe = Pipeline([ ... ('select',...8]} >>> search = GridSearchCV(pipe, param_grid, cv=5).fit(X, y)...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
preprocessing.rst.txt
random_state=42) >>> pipe = make_pipeline(StandardScaler(),..., LogisticRegression()) >>> pipe.fit(X_train, y_train) # apply...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
index.rst.txt
/thumb/sphx_glr_plot_digits_pipe_thumb.png :alt: :ref:`sphx_...xamples_compose_plot_digits_pipe.py` .. raw:: html <div clas...scikit-learn.org/stable/_sources/auto_examples/index.rst.txt -
feature_extraction.rst.txt
classifier (maybe after being piped into a :class:`~text.TfidfTransformer`...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
neighbors.rst.txt
KNeighborsClassifier(n_neighbors=3) >>> nca_pipe = Pipeline([('nca', nca), ('knn',...('knn', knn)]) >>> nca_pipe.fit(X_train, y_train) Pipeline(...)...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
plot_release_highlights_1_4_0.rst.txt
the latest version (with pip):: pip install --upgrade scikit-learn...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_4_0.r... -
install.rst.txt
id="quickstart-pip" checked> <label for="quickstart-pip">pip</label>...data-packager="pip" data-os="linux" data-venv="no" ><span>pip3 install...scikit-learn.org/stable/_sources/install.rst.txt