slickml.visualization._selection#

Module Contents#

Functions#

plot_xfs_cv_results(, internalcvcolor, ...)

Visualizies the cross-validation results of XGBoostFeatureSelector.

plot_xfs_feature_frequency(, show_freq_pct, color, ...)

Visualizes the selected features frequency as a bar chart.

slickml.visualization._selection.plot_xfs_cv_results(*, figsize: Optional[Tuple[Union[int, float], Union[int, float]]] = (10, 8), internalcvcolor: Optional[str] = '#4169E1', externalcvcolor: Optional[str] = '#8A2BE2', sharex: Optional[bool] = False, sharey: Optional[bool] = False, save_path: Optional[str] = None, display_plot: Optional[bool] = True, return_fig: Optional[bool] = False, **kwargs: Dict[str, Any]) Optional[matplotlib.figure.Figure][source]#

Visualizies the cross-validation results of XGBoostFeatureSelector.

Notes

It visualizes the internal and external cross-validiation performance during the selection process. The internal refers to the performance of the train/test folds during the xgboost.cv() using metrics rounds to help the best number of boosting round while the external refers to the performance of xgboost.train() based on watchlist using eval_metric. Additionally, sns.distplot previously was used which is now deprecated. More details in [seaborn-distplot-deprecation].

Parameters:
  • figsize (tuple, optional) – Figure size, by default (10, 8)

  • internalcvcolor (str, optional) – Color of the histograms for internal cv results, by default “#4169E1”

  • externalcvcolor (str, optional) – Color of the histograms for external cv results, by default “#8A2BE2”

  • sharex (bool, optional) – Whether to share “X” axis for each column of subplots, by default False

  • sharey (bool, optional) – Whether to share “Y” axis for each row of subplots, by default False

  • save_path (str, optional) – The full or relative path to save the plot including the image format such as “myplot.png” or “../../myplot.pdf”, by default None

  • display_plot (bool, optional) – Whether to show the plot, by default True

  • return_fig (bool, optional) – Whether to return figure object, by default False

  • kwargs (Dict[str, Any]) – Required plooting elements (plotting_cv_ attribute of XGBoostFeatureSelector)

See also

slickml.selection.XGBoostFeatureSelector, Refereces, ---------,

Returns:

Figure, optional

slickml.visualization._selection.plot_xfs_feature_frequency(freq: pandas.DataFrame, *, figsize: Optional[Tuple[Union[int, float], Union[int, float]]] = (8, 4), show_freq_pct: Optional[bool] = True, color: Optional[str] = '#87CEEB', marker: Optional[str] = 'o', markersize: Optional[Union[int, float]] = 10, markeredgecolor: Optional[str] = '#1F77B4', markerfacecolor: Optional[str] = '#1F77B4', markeredgewidth: Optional[Union[int, float]] = 1, fontsize: Optional[Union[int, float]] = 12, save_path: Optional[str] = None, display_plot: Optional[bool] = True, return_fig: Optional[bool] = False) Optional[matplotlib.figure.Figure][source]#

Visualizes the selected features frequency as a bar chart.

This plotting function can be used along with feature_frequency_ attribute of any frequency-based feature selection algorithm such as XGBoostFeatureSelector.

feature importancepd.DataFrame

Feature importance (feature_frequency_ attribute)

figsizetuple, optional

Figure size, by default (8, 4)

show_freq_pctbool, optional

Whether to show the features frequency in percent, by default True

colorstr, optional

Color of the horizontal lines of lollipops, by default “#87CEEB”

markerstr, optional

Marker style of the lollipops. More valid marker styles can be found at [markers-api], by default “o”

markersizeUnion[int, float], optional

Markersize, by default 10

markeredgecolorstr, optional

Marker edge color, by default “#1F77B4”

markerfacecolorstr, optional

Marker face color, by defualt “#1F77B4”

markeredgewidthUnion[int, float], optional

Marker edge width, by default 1

fontsizeUnion[int, float], optional

Fontsize for xlabel and ylabel, and ticks parameters, by default 12

save_pathstr, optional

The full or relative path to save the plot including the image format such as “myplot.png” or “../../myplot.pdf”, by default None

display_plotbool, optional

Whether to show the plot, by default True

return_figbool, optional

Whether to return figure object, by default False

References

Returns:

Figure, optional