mfeat-factors dataset visualizationΒΆ

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

  • Target distribution
  • F=1.06E+03, F=7.18E+02, F=7.16E+02, F=6.95E+02, F=6.64E+02, F=6.60E+02, F=6.58E+02, F=6.29E+02, F=6.12E+02, F=5.59E+02
  • Top feature interactions, 0.542, 0.537, 0.537, 0.535
  • Discriminating PCA directions, 0.563, 0.517, 0.512, Scree plot (PCA explained variance)
  • Discriminating LDA directions, 0.758, 0.740, 0.735, 0.728


/home/circleci/miniconda/envs/testenv/lib/python3.8/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.
  warn("Multiple active versions of the dataset matching the name"
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 10.001 seconds)

Gallery generated by Sphinx-Gallery