Human Activity Recognition VisualizationΒΆ

  • Target distribution
  • F=5.08E+04, F=4.63E+04, F=4.44E+04, F=4.12E+04, F=4.04E+04, F=3.75E+04, F=3.26E+04, F=3.25E+04, F=3.22E+04, F=3.13E+04
  • Top feature interactions, 0.691, 0.686, 0.683, 0.683
  • Discriminating PCA directions, 0.649, 0.612, 0.571, Scree plot (PCA explained variance)
  • Discriminating LDA directions, 0.863, 0.830, 0.806, 0.787

Out:

Target looks like classification
Showing only top 10 of 561 continuous features
Linear Discriminant Analysis training set score: 0.984

# sphinx_gallery_thumbnail_number = 3
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_openml
from dabl import plot

X, y = fetch_openml('har', as_frame=True, return_X_y=True)

plot(X, y)
plt.show()

Total running time of the script: ( 0 minutes 24.735 seconds)

Gallery generated by Sphinx-Gallery