mfeat-factors dataset visualizationΒΆ

A multiclass dataset with 10 classes. Linear discriminant analysis works surprisingly well!

  • ../../_images/sphx_glr_plot_mfeat_factors_001.png
  • ../../_images/sphx_glr_plot_mfeat_factors_002.png
  • ../../_images/sphx_glr_plot_mfeat_factors_003.png
  • ../../_images/sphx_glr_plot_mfeat_factors_004.png
  • ../../_images/sphx_glr_plot_mfeat_factors_005.png


/home/circleci/miniconda/envs/testenv/lib/python3.7/site-packages/sklearn/datasets/ UserWarning: Multiple active versions of the dataset matching the name mfeat-factors exist. Versions may be fundamentally different, returning version 1.
  " {version}.".format(name=name, version=res[0]['version']))
Target looks like classification
Showing only top 10 of 216 continuous features
Linear Discriminant Analysis training set score: 0.993

# sphinx_gallery_thumbnail_number = 5
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_openml
from dabl import plot

X, y = fetch_openml('mfeat-factors', as_frame=True, return_X_y=True)

plot(X, y)

Total running time of the script: ( 0 minutes 10.114 seconds)

Gallery generated by Sphinx-Gallery