Files
PHANTOM/experiments/procesing/pipeline.py
2025-11-22 21:09:04 +01:00

21 lines
582 B
Python

from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from extract import DataExtractor
from mapping import SessionTransitionProbMatrixTransformer, render_graph
from demand import DemandEstimator
# exposable pipelines
etl_pipeline = Pipeline([
('data_extraction', DataExtractor()),
])
pricing_pipeline = Pipeline([
('demand_estimation', DemandEstimator()),
('scaling', StandardScaler()),
])
if __name__ == "__main__":
processed_data = etl_pipeline.fit_transform(None)
pricing = pricing_pipeline.fit_transform(processed_data)