This example simulates a multi-label document classification problem. The dataset is generated randomly based on the following process: pick

This example illustrates the effect of the parameters gamma and C of the Radial Basis Function (RBF) kernel SVM. Intuitively, the gamma

Performs a pixel-wise Vector Quantization (VQ) of an image of the summer palace (China), reducing the number of colors required to show the image from 96,615

Demonstrates the effect of different metrics on the hierarchical clustering. The example is engineered to show the effect of the choice

For greyscale image data where pixel values can be interpreted as degrees of blackness on a white background, like handwritten

Sample usage of Nearest Centroid classification. It will plot the decision boundaries for each class.

Plot the decision boundaries of a VotingClassifier for two features of the Iris dataset. Plot the class probabilities

This example aims at showing characteristics of different clustering algorithms on datasets that are ?interesting? but still in 2D

This example compares the timing of Birch (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 100,000 samples and

Datasets can often contain components of that require different feature extraction and processing pipelines. This scenario might occur when: