- Sort Score
- Num 10 results
- Language All
- Labels All
Results 991 - 1000 of 2,722 for document (0.71 seconds)
Filter
-
Compare Stochastic learning strategies for MLPC...
This example visualizes some training loss curves for different stochastic learning strategies, including SGD and Adam. Because of time-constraints, we use several small datasets, for which L-BFGS ...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_training_curves.html -
Effect of transforming the targets in regressio...
In this example, we give an overview of TransformedTargetRegressor. We use two examples to illustrate the benefit of transforming the targets before learning a linear regression model. The first ex...scikit-learn.org/stable/auto_examples/compose/plot_transformed_target.html -
Varying regularization in Multi-layer Perceptro...
A comparison of different values for regularization parameter ‘alpha’ on synthetic datasets. The plot shows that different alphas yield different decision functions. Alpha is a parameter for regula...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_alpha.html -
Multilabel classification using a classifier ch...
This example shows how to use ClassifierChain to solve a multilabel classification problem. The most naive strategy to solve such a task is to independently train a binary classifier on each label ...scikit-learn.org/stable/auto_examples/multioutput/plot_classifier_chain_yeast.html -
Test with permutations the significance of a cl...
This example demonstrates the use of permutation_test_score to evaluate the significance of a cross-validated score using permutations. Dataset: We will use the Iris plants dataset, which consists ...scikit-learn.org/stable/auto_examples/model_selection/plot_permutation_tests_for_classification.html -
Concatenating multiple feature extraction metho...
In many real-world examples, there are many ways to extract features from a dataset. Often it is beneficial to combine several methods to obtain good performance. This example shows how to use Feat...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html -
2.7. Novelty and Outlier Detection — scikit-lea...
Many applications require being able to decide whether a new observation belongs to the same distribution as existing observations (it is an inlier), or should be considered as different (it is an ...scikit-learn.org/stable/modules/outlier_detection.html -
Pipelining: chaining a PCA and a logistic regre...
The PCA does an unsupervised dimensionality reduction, while the logistic regression does the prediction. We use a GridSearchCV to set the dimensionality of the PCA, Total running time of the scrip...scikit-learn.org/stable/auto_examples/compose/plot_digits_pipe.html -
1.14. Semi-supervised learning — scikit-learn 1...
Semi-supervised learning is a situation in which in your training data some of the samples are not labeled. The semi-supervised estimators in sklearn.semi_supervised are able to make use of this ad...scikit-learn.org/stable/modules/semi_supervised.html -
Comparing different hierarchical linkage method...
This example shows characteristics of different linkage methods for hierarchical clustering on datasets that are “interesting” but still in 2D. The main observations to make are: single linkage is ...scikit-learn.org/stable/auto_examples/cluster/plot_linkage_comparison.html