- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 851 - 860 of 1,682 for document (0.93 sec)
-
adjusted_mutual_info_score — scikit-learn 1.6.1...
Gallery examples: A demo of K-Means clustering on the handwritten digits data Adjustment for chance in clustering performance evaluation Demo of DBSCAN clustering algorithm Demo of affinity propaga...scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_mutual_info_score.html -
Gaussian Processes regression: basic introducto...
A simple one-dimensional regression example computed in two different ways: A noise-free case, A noisy case with known noise-level per datapoint. In both cases, the kernel’s parameters are estimate...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy_targets.html -
Hierarchical clustering: structured vs unstruct...
Example builds a swiss roll dataset and runs hierarchical clustering on their position. For more information, see Hierarchical clustering. In a first step, the hierarchical clustering is performed ...scikit-learn.org/stable/auto_examples/cluster/plot_ward_structured_vs_unstructured.html -
MNIST classification using multinomial logistic...
Here we fit a multinomial logistic regression with L1 penalty on a subset of the MNIST digits classification task. We use the SAGA algorithm for this purpose: this a solver that is fast when the nu...scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html -
What to know on Pope Francis' funeral and how a...
will also draw from a 20-page document called the “ Universi Dominici...papal ring to seal a false document,” Collins said. Once a new...www.nbcnews.com/news/world/pope-francis-dead-what-happens-next-rcna128745 -
1.4. Support Vector Machines — scikit-learn 1.6...
Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection. The advantages of support vector machines are: Effective in high ...scikit-learn.org/stable/modules/svm.html -
mean_absolute_percentage_error — scikit-learn 1...
Gallery examples: Lagged features for time series forecastingscikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_percentage_error.html -
d2_log_loss_score — scikit-learn 1.6.1 document...
Skip to main content Back to top Ctrl + K GitHub Choose version d2_log_loss_score # sklearn.metrics. d2_log_loss_scor...scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_log_loss_score.html -
Balance model complexity and cross-validated sc...
This example balances model complexity and cross-validated score by finding a decent accuracy within 1 standard deviation of the best accuracy score while minimising the number of PCA components [1...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_refit_callable.html -
Joint feature selection with multi-task Lasso —...
The multi-task lasso allows to fit multiple regression problems jointly enforcing the selected features to be the same across tasks. This example simulates sequential measurements, each task is a t...scikit-learn.org/stable/auto_examples/linear_model/plot_multi_task_lasso_support.html