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(
)
