Libsvm GUI
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

A simple graphical frontend for Libsvm mainly intended for didactic purposes. You can create data points by point and click and visualize the decision region induced by different

2025-01-10 15:47:30
Out-of-core classification of text documents
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

This is an example showing how scikit-learn can be used for classification using an out-of-core approach: learning from data that doesn?t fit into

2025-01-10 15:47:30
Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

This is an example of applying Non-negative Matrix Factorization and Latent Dirichlet Allocation on a

2025-01-10 15:47:30
Model Complexity Influence
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

Demonstrate how model complexity influences both prediction accuracy and computational performance. The dataset is the Boston Housing dataset (resp. 20 Newsgroups)

2025-01-10 15:47:30
Outlier detection on a real data set
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

This example illustrates the need for robust covariance estimation on a real data set. It is useful both for outlier detection and for a better understanding

2025-01-10 15:47:30
Faces recognition example using eigenfaces and SVMs
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

The dataset used in this example is a preprocessed excerpt of the ?Labeled Faces in the Wild?, aka

2025-01-10 15:47:30
Prediction Latency
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

This is an example showing the prediction latency of various scikit-learn estimators. The goal is to measure the latency one can expect when doing predictions either

2025-01-10 15:47:30
Species distribution modeling
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

Modeling species? geographic distributions is an important problem in conservation biology. In this example we model the geographic distribution of two south american

2025-01-10 15:47:30
Visualizing the stock market structure
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

This example employs several unsupervised learning techniques to extract the stock market structure from variations in historical quotes. The quantity

2025-01-10 15:47:30
Compressive sensing
  • References/Python/scikit-learn/Examples/Examples based on real world datasets

This example shows the reconstruction of an image from a set of parallel projections, acquired along different angles. Such

2025-01-10 15:47:30