Choosing the number of components
You'll now make a more informed decision on the number of principal components to reduce your data to using the "elbow in the plot" technique. One last time, you'll work on the numeric ANSUR female dataset pre-loaded as ansur_df.
All relevant packages and classes have been pre-loaded for you (Pipeline(), StandardScaler(), PCA()).
Deze oefening maakt deel uit van de cursus
Dimensionality Reduction in Python
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Pipeline a scaler and PCA selecting 10 components
pipe = ____([('scaler', ____),
('reducer', ____)])