def bde(ctx): delete_cached_model() click.echo("Decision engine cache deleted") delete_previous_analysis_reports() click.echo("Analysis reports deleted") get_decision_engine(get_ml_data()) click.echo("Decision engine created")
def dea(ctx): delete_previous_analysis_reports() click.echo("Analysis reports deleted") ml_data = get_ml_data() decision_engine = get_decision_engine(ml_data) analyzer = DecisionEngineAnalyzer(decision_engine, ml_data) analyzer.create_analysis_reports() click.echo("Reports created in directory %s" % ANALYSIS_RESULTS_DIR)
import logging from data_processing.ml_data_prepairer import get_ml_data from models.build_decision_engine import get_decision_engine from models.analysis.decision_engine_analyzer import DecisionEngineAnalyzer logger = logging.getLogger() logger.setLevel(logging.INFO) congestive_heart_failure_data = get_ml_data() decision_engine = get_decision_engine(congestive_heart_failure_data) decision_engine_analyzer = DecisionEngineAnalyzer(decision_engine, congestive_heart_failure_data) print("Important Features for outcome prediction") print(decision_engine.get_outcome_feature_importance().sort_values('importance', ascending=False)) print("Important Features for actual treatment prediction") print(decision_engine.get_actual_treatment_feature_importance().sort_values('importance', ascending=False)) recommended_treatment_overview = decision_engine_analyzer.get_recommended_treatment_overview() print('Recommended treatment overview') print(recommended_treatment_overview) outcome_changes = decision_engine_analyzer.get_outcome_change_by_recommended_and_actual_treatment() print('Recommended treatment counts per actual treatment') print(outcome_changes) top_treatment_improvements = outcome_changes[(outcome_changes.counts > 20) & (outcome_changes.survival_rate_improvement > 0.025)] print("Top opportunities for treatment improvements")
import logging from data_processing.ml_data_prepairer import get_ml_data from models.build_decision_engine import get_decision_engine from models.analysis.decision_engine_analyzer import DecisionEngineAnalyzer logger = logging.getLogger() logger.setLevel(logging.INFO) congestive_heart_failure_data = get_ml_data() decision_engine = get_decision_engine(congestive_heart_failure_data) decision_engine_analyzer = DecisionEngineAnalyzer( decision_engine, congestive_heart_failure_data) print("Important Features for outcome prediction") print(decision_engine.get_outcome_feature_importance().sort_values( 'importance', ascending=False)) print("Important Features for actual treatment prediction") print(decision_engine.get_actual_treatment_feature_importance().sort_values( 'importance', ascending=False)) recommended_treatment_overview = decision_engine_analyzer.get_recommended_treatment_overview( ) print('Recommended treatment overview') print(recommended_treatment_overview) outcome_changes = decision_engine_analyzer.get_outcome_change_by_recommended_and_actual_treatment( )