slickml.visualization._glmnet#

Module Contents#

Functions#

plot_glmnet_coeff_path(, linestyle, fontsize, ...)

Visualizes the GLMNet coefficients' paths.

plot_glmnet_cv_results(, marker, markersize, ...)

Visualizes the GLMNet cross-validation results.
slickml.visualization._glmnet.plot_glmnet_coeff_path(figsize: Optional[Tuple[Union[int, float], Union[int, float]]] = (8, 5), linestyle: Optional[str] = '-', fontsize: Optional[Union[int, float]] = 12, grid: Optional[bool] = True, legend: Optional[bool] = True, legendloc: Optional[Union[int, str]] = 'center', xlabel: Optional[str] = None, ylabel: Optional[str] = 'Coefficients', title: Optional[str] = None, bbox_to_anchor: Tuple[float, float] = (1.1, 0.5), yscale: Optional[str] = 'linear', save_path: Optional[str] = None, display_plot: Optional[bool] = True, return_fig: Optional[bool] = False, **kwargs: Dict[str, Any]) → Optional[matplotlib.figure.Figure][source]#

Visualizes the GLMNet coefficients’ paths.

Parameters:

  • figsize (tuple, optional) – Figure size, by default (8, 5)

  • linestyle (str, optional) – Linestyle of paths, by default “-”

  • fontsize (Union[int, float], optional) – Fontsize of the title. The fontsizes of xlabel, ylabel, tick_params, and legend are resized with 0.85, 0.85, 0.75, and 0.85 fraction of title fontsize, respectively, by default 12

  • grid (bool, optional) – Whether to show (x,y) grid on the plot or not, by default True

  • legend (bool, optional) – Whether to show legend on the plot or not, by default True

  • legendloc (Union[int, str], optional) – Location of legend, by default “center”

  • xlabel (str, optional) – Xlabel of the plot, by default “-Log(Lambda)”

  • ylabel (str, optional) – Ylabel of the plot, by default “Coefficients”

  • title (str, optional) – Title of the plot, by default “Best {lambda_best} with {n} Features”

  • yscale (str, optional) – Scale for y-axis (coefficients). Possible options are "linear", "log", "symlog", "logit" [yscale], by default “linear”

  • bbox_to_anchor (Tuple[float, float], optional) – Relative coordinates for legend location outside of the plot, by default (1.1, 0.5)

  • 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]) – Key-value pairs of results. results_ attribute can be used

References

Returns:

Figure, optional

slickml.visualization._glmnet.plot_glmnet_cv_results(figsize: Optional[Tuple[Union[int, float], Union[int, float]]] = (8, 5), marker: Optional[str] = 'o', markersize: Optional[Union[int, float]] = 5, color: Optional[str] = 'red', errorbarcolor: Optional[str] = 'black', maxlambdacolor: Optional[str] = 'purple', bestlambdacolor: Optional[str] = 'navy', linestyle: Optional[str] = '--', fontsize: Optional[Union[int, float]] = 12, grid: Optional[bool] = True, legend: Optional[bool] = True, legendloc: Optional[Union[int, str]] = 'best', xlabel: Optional[str] = None, ylabel: Optional[str] = None, title: Optional[str] = None, save_path: Optional[str] = None, display_plot: Optional[bool] = True, return_fig: Optional[bool] = False, **kwargs: Dict[str, Any]) → Optional[matplotlib.figure.Figure][source]#

Visualizes the GLMNet cross-validation results.

Notes

This plotting function can be used along with results_ attribute of any of GLMNetCVClassifier, or GLMNetCVRegressor classes as kwargs.

Parameters:

  • figsize (tuple, optional) – Figure size, by default (8, 5)

  • marker (str, optional) – Marker style of the metric to distinguish the error bars. More valid marker styles can be found at [markers-api], by default “o”

  • markersize (Union[int, float], optional) – Markersize, by default 5

  • color (str, optional) – Line and marker color, by default “red”

  • errorbarcolor (str, optional) – Error bar color, by default “black”

  • maxlambdacolor (str, optional) – Color of vertical line for lambda_max_, by default “purple”

  • bestlambdacolor (str, optional) – Color of vertical line for lambda_best_, by default “navy”

  • linestyle (str, optional) – Linestyle of vertical lambda lines, by default “–”

  • fontsize (Union[int, float], optional) – Fontsize of the title. The fontsizes of xlabel, ylabel, tick_params, and legend are resized with 0.85, 0.85, 0.75, and 0.85 fraction of title fontsize, respectively, by default 12

  • grid (bool, optional) – Whether to show (x,y) grid on the plot or not, by default True

  • legend (bool, optional) – Whether to show legend on the plot or not, by default True

  • legendloc (Union[int, str], optional) – Location of legend, by default “best”

  • xlabel (str, optional) – Xlabel of the plot, by default “-Log(Lambda)”

  • ylabel (str, optional) – Ylabel of the plot, by default “{n_splits}-Folds CV Mean {metric}”

  • title (str, optional) – Title of the plot, by default “Best {lambda_best} with {n} Features”

  • 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]) – Key-value pairs of results. results_ attribute can be used

See also

slickml.classification.GLMNetCVClassifier, slickml.regression.GLMNetCVRegressor

References

Returns:

Figure, optional