 sklearn.datasets.make_circles   sklearn.datasets.make_circles(n_samples=100, *, shuffle=True, noise=None, random_state=None, factor=0.8)[source]
 
Make a large circle containing a smaller circle in 2d. A simple toy dataset to visualize clustering and classification algorithms. Read more in the User Guide.  Parameters:
 
 
n_samplesint or tuple of shape (2,), dtype=int, default=100


If int, it is the total number of points generated. For odd numbers, the inner circle will have one point more than the outer circle. If two-element tuple, number of points in outer circle and inner circle.  Changed in version 0.23: Added two-element tuple.   
shufflebool, default=True


Whether to shuffle the samples.  
noisefloat, default=None


Standard deviation of Gaussian noise added to the data.  
random_stateint, RandomState instance or None, default=None


Determines random number generation for dataset shuffling and noise. Pass an int for reproducible output across multiple function calls. See Glossary.  
factorfloat, default=.8


Scale factor between inner and outer circle in the range (0, 1).    Returns:
 
 
Xndarray of shape (n_samples, 2)


The generated samples.  
yndarray of shape (n_samples,)


The integer labels (0 or 1) for class membership of each sample.     
  Examples using sklearn.datasets.make_circles
 

 Classifier comparison 

 Comparing different clustering algorithms on toy datasets 

 Comparing different hierarchical linkage methods on toy datasets 

 Kernel PCA 

 Hashing feature transformation using Totally Random Trees 

 t-SNE: The effect of various perplexity values on the shape 

 Compare Stochastic learning strategies for MLPClassifier 

 Varying regularization in Multi-layer Perceptron 

 Feature discretization 

 Label Propagation learning a complex structure 

 

    
{'path': 'public/docs/scikit_learn/modules/generated/sklearn.datasets.make_circles.html', 'source': 'DevDocs.IO'}