logml.report.controllers.survival_analysis

Classes

SurvivalAnalysisController(cfg, global_params)

Implements data handling and plotting API for SurvivalAnalysis results.

class logml.report.controllers.survival_analysis.SurvivalAnalysisController(cfg: GlobalConfig, global_params: dict, setup_id: str = '')

Bases: object

Implements data handling and plotting API for SurvivalAnalysis results.

show_target_overview(): Shows SA problem definition.

get_km_summary() → pandas.core.frame.DataFrame: Returns a summary produced by Kaplan-Meier SA method.

show_km_plots(show_table_only=False, top_k: Optional[int] = None): Plots the results produced by Kaplan-Meier SA method. Summary table and Kaplan-Meier plots for the top K markers.

get_oc_summary() → pandas.core.frame.DataFrame: Returns a summary produced by Optimal Cut Off SA method.

show_oc_plots(top_k: Optional[int] = None): Plots the results produced by Optimal Cut Off SA method. Summary table and OptimalCutOff (+Kaplan-Meier) plots for the top K markers.

get_cox_history() → pandas.core.frame.DataFrame: Returns a history artifact produced by Cox SA method.

show_initial_cox_summary(): Shows the initial number of features for Cox.

show_initial_cox_model(): Displays the initial Cox model.

show_cox_backward_path_summary(): Shows the Cox’s backward path summary: the number of features removed.

show_cox_forward_path_summary(): Shows the Cox’s forward path summary: the number of features added back.

show_final_cox_model(): Displays the final Cox model.