elphick.sklearn_viz.features.outlier_detection.plot_outlier_matrix

elphick.sklearn_viz.features.outlier_detection.plot_outlier_matrix(x, pca_spec=0, p_val=0.001, principal_components=False)[source]

Detect and plot outliers

Parameters:

x (DataFrame) – X values for outlier detection.
pca_spec (Union[float, int]) – If zero, pca is not used. For integers (n) > 0 outlier detection is performed on the top n principal components. For values (f) < 1, outlier detection is performed on the number of principal components that explain f% of the variance.
p_val (float) – the p-value threshold for outlier detection.
principal_components (bool) – If True (and pca_spec is not 0) the principal components will be plotted. Otherwise, will plot in the original feature space.

Return type:

Figure