Plot N clusters after PCA

gistfile1.txt

# from https://github.com/ogrisel/parallel_ml_tutorial/blob/master/rendered_notebooks/05%20-%20Model%20Selection%20and%20Assessment.ipynb

from itertools import cycle

colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
markers = ['+', 'o', '^', 'v', '<', '>', 'D', 'h', 's']
for i, c, m in zip(np.unique(y), cycle(colors), cycle(markers)):
    plt.scatter(X_pca[y == i, 0], X_pca[y == i, 1],
        c=c, marker=m, label=i, alpha=0.5)
    
_ = plt.legend(loc='best')