Classifier comparison
  • References/Python/scikit-learn/Examples/Classification

A comparison of a several classifiers in scikit-learn on synthetic datasets. The point of this example is to illustrate the nature of decision boundaries of different

2025-01-10 15:47:30
Logistic Regression 3-class Classifier
  • References/Python/scikit-learn/Examples/Generalized Linear Models

Show below is a logistic-regression classifiers decision boundaries on the

2025-01-10 15:47:30
Plot randomly generated multilabel dataset
  • References/Python/scikit-learn/Examples/Dataset examples

This illustrates the datasets.make_multilabel_classification dataset generator. Each sample consists of counts of two features (up to

2025-01-10 15:47:30
Recursive feature elimination
  • References/Python/scikit-learn/Examples/Feature Selection

A recursive feature elimination example showing the relevance of pixels in a digit classification task.

2025-01-10 15:47:30
SVM Exercise
  • References/Python/scikit-learn/Examples/Tutorial exercises

A tutorial exercise for using different SVM kernels. This exercise is used in the

2025-01-10 15:47:30
Illustration of prior and posterior Gaussian process for different kernels
  • References/Python/scikit-learn/Examples/Gaussian Process for Machine Learning

This example illustrates the prior and posterior of a GPR with different kernels. Mean, standard deviation, and 10

2025-01-10 15:47:30
Label Propagation digits
  • References/Python/scikit-learn/Examples/Semi Supervised Classification

This example demonstrates the power of semisupervised learning by training a Label Spreading model to classify handwritten digits with sets

2025-01-10 15:47:30
Iso-probability lines for Gaussian Processes classification
  • References/Python/scikit-learn/Examples/Gaussian Process for Machine Learning

A two-dimensional classification example showing iso-probability lines for the predicted probabilities.

2025-01-10 15:47:30
Polynomial interpolation
  • References/Python/scikit-learn/Examples/Generalized Linear Models

This example demonstrates how to approximate a function with a polynomial of degree n_degree by using ridge regression. Concretely, from n_samples 1d points, it suffices

2025-01-10 15:47:30
Nearest Neighbors regression
  • References/Python/scikit-learn/Examples/Nearest Neighbors

Demonstrate the resolution of a regression problem using a k-Nearest Neighbor and the interpolation of the target using both barycenter and constant weights.

2025-01-10 15:47:30