Theil-Sen Regression
  • References/Python/scikit-learn/Examples/Generalized Linear Models

Computes a Theil-Sen Regression on a synthetic dataset. See

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Feature agglomeration
  • References/Python/scikit-learn/Examples/Clustering

These images how similar features are merged together using feature agglomeration.

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Decision Tree Regression with AdaBoost
  • References/Python/scikit-learn/Examples/Ensemble methods

A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D sinusoidal dataset with a small amount of Gaussian noise. 299 boosts (300 decision

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A demo of the Spectral Co-Clustering algorithm
  • References/Python/scikit-learn/Examples/Biclustering

This example demonstrates how to generate a dataset and bicluster it using the Spectral Co-Clustering algorithm. The dataset is generated

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Plot multinomial and One-vs-Rest Logistic Regression
  • References/Python/scikit-learn/Examples/Generalized Linear Models

Plot decision surface of multinomial and One-vs-Rest Logistic Regression. The hyperplanes corresponding to the three One-vs-Rest (OVR) classifiers

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Outlier detection with several methods.
  • References/Python/scikit-learn/Examples/Covariance estimation

When the amount of contamination is known, this example illustrates three different ways of performing

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Plot multi-class SGD on the iris dataset
  • References/Python/scikit-learn/Examples/Generalized Linear Models

Plot decision surface of multi-class SGD on iris dataset. The hyperplanes corresponding to the three one-versus-all (OVA) classifiers are represented

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Simple 1D Kernel Density Estimation
  • References/Python/scikit-learn/Examples/Nearest Neighbors

This example uses the

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SGD: Maximum margin separating hyperplane
  • References/Python/scikit-learn/Examples/Generalized Linear Models

Plot the maximum margin separating hyperplane within a two-class separable dataset using a linear Support Vector Machines classifier trained using SGD

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The Johnson-Lindenstrauss bound for embedding with random projections
  • References/Python/scikit-learn/Examples/General examples

The

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