- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 1 - 10 of 24 for text (0.09 sec)
-
linear_model.rst.txt
cost of :math:`O(n_{\text{samples}} n_{\text{features}}^2)`, assuming...that :math:`n_{\text{samples}} \geq n_{\text{features}}`. .....scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
about.rst.txt
|aphp| image:: images/logo_APHP_text.png :width: 150pt :target: https://aphp.fr/... .. raw :: html <div style="text-align: center;"> <a class="btn...scikit-learn.org/stable/_sources/about.rst.txt -
cross_validation.rst.txt
available data as a **test set** ``X_test, y_test``. Note that the...>>> X_train, X_test, y_train, y_test = train_test_split( ... X,...scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt -
feature_extraction.rst.txt
:math:`\text{tf-idf}_{\text{term1}} = \text{tf} \times \text{idf}...:math:`\text{tf-idf(t,d)}=\text{tf(t,d)} \times \text{idf(t)}`....scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
governance.rst.txt
.. _governance: ========== Scikit-learn governance and decision-making ========== The purpose of this document is to formalize the governance process used by the scikit-learn project, to clarify ho...scikit-learn.org/stable/_sources/governance.rst.txt -
feature_selection.rst.txt
based on univariate statistical tests. It can be seen as a preprocessing...common univariate statistical tests for each feature: false positive...scikit-learn.org/stable/_sources/modules/feature_selection.rst.txt -
classes.rst.txt
_text_feature_extraction_ref: From text --------- .....feature_extraction.text.CountVectorizer feature_extraction.text.HashingVectorizer...scikit-learn.org/stable/_sources/modules/classes.rst.txt -
plot_release_highlights_1_4_0.rst.txt
X_test, y_train, y_test = train_test_split(X_adult,...--sklearn-color-text-on-default-background: var(--sg-text-color, va...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_4_0.r... -
preprocessing.rst.txt
K_{test} - 1'_{\text{n}_{samples}} K - K_{test} 1_{\text{n}_{samples}}...>>> X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
clustering.rst.txt
math:: \text{ARI} = \frac{\text{RI} - E[\text{RI}]}{\max(\text{RI})...math:: \text{AMI} = \frac{\text{MI} - E[\text{MI}]}{\text{mean}(H(U),...scikit-learn.org/stable/_sources/modules/clustering.rst.txt