plot_pca

---

method plot_pca(title=None, figsize=(10, 6), filename=None, display=True) [source]

Plot the explained variance ratio vs the number of components. Only available if PCA was applied on the data.

Parameters:

title: str or None, optional (default=None) Plot's title. If None, the title is left empty. figsize: tuple, optional (default=(10, 6)) Figure's size, format as (x, y). filename: str or None, optional (default=None) Name of the file. Use "auto" for automatic naming. If None, the figure is not saved. display: bool or None, optional (default=True) Whether to render the plot. If None, it returns the matplotlib figure.

Returns:

fig: matplotlib.figure.Figure Plot object. Only returned if display=None.

Example

from atom import ATOMClassifier

atom = ATOMClassifier(X, y)
atom.feature_selection(strategy="PCA", n_features=11)
atom.plot_pca()