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7. Dataset transformations — scikit-learn...
scikit-learn provides a library of transformers, which may clean (see Preprocessing data), reduce (see Unsupervised dimensionality reduction), expand (see Kernel Approximation) or generate (see Fea...scikit-learn.org/stable/data_transforms.html -
Probability Calibration curves — scikit-l...
When performing classification one often wants to predict not only the class label, but also the associated probability. This probability gives some kind of confidence on the prediction. This examp...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html -
Compare BIRCH and MiniBatchKMeans — sciki...
This example compares the timing of BIRCH (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 25,000 samples and 2 features generated using make_blobs. B...scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html -
Model Complexity Influence — scikit-learn...
Demonstrate how model complexity influences both prediction accuracy and computational performance. We will be using two datasets:,- Diabetes dataset for regression. This dataset consists of 10 mea...scikit-learn.org/stable/auto_examples/applications/plot_model_complexity_influence.html -
Wikipedia principal eigenvector — scikit-...
A classical way to assert the relative importance of vertices in a graph is to compute the principal eigenvector of the adjacency matrix so as to assign to each vertex the values of the components ...scikit-learn.org/stable/auto_examples/applications/wikipedia_principal_eigenvector.html -
Semi Supervised Classification — scikit-l...
Examples concerning the sklearn.semi_supervised module. Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset Effect of varying threshold for self-training Label Propagati...scikit-learn.org/stable/auto_examples/semi_supervised/index.html -
Glossary of Common Terms and API Elements ̵...
other relevant parts of the documentation which do so. By linking...overviewed in the contributor documentation . The specific interfaces...scikit-learn.org/stable/glossary.html -
Gradient Boosting Out-of-Bag estimates — ...
Out-of-bag (OOB) estimates can be a useful heuristic to estimate the “optimal” number of boosting iterations. OOB estimates are almost identical to cross-validation estimates but they can be comput...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html -
1.4. Support Vector Machines — scikit-lea...
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 -
Online learning of a dictionary of parts of fac...
This example uses a large dataset of faces to learn a set of 20 x 20 images patches that constitute faces. From the programming standpoint, it is interesting because it shows how to use the online ...scikit-learn.org/stable/auto_examples/cluster/plot_dict_face_patches.html