<jupyter_start><jupyter_text>SET TRAIN & TEST VOLUME  build dataset for one month<jupyter_code>from util.build_dataset import build_master

dataset = build_master(bucket_name="production-bobsim", dataset="process_fmp", date="201908", pipe_data=False)
from analysis.food_material_price.research import *
rmse_by_test_size(dataset, train_size=10)<jupyter_output>2020-04-22 19:16:33:manage:<INFO> success to download from 'food_material_price_predict_model/research/tuned_params.pkl'
C:\BOBSIM\production-bobsim-python\src\main\python\analysis\food_material_price\research.py:159: UserWarning: With alpha=0, this algorithm does not converge well. You are advised to use the LinearRegression estimator
  regr.fit(x_train, y_train)
C:\Users\jinho\Anaconda3\envs\BOBSIM\lib\site-packages\sklearn\linear_model\_coordinate_descent.py:476: UserWarning: Coordinate descent with no regularization may lead to unexpected results and is discouraged.
  positive)
C:\Users\jinho\Anaconda3\envs\BOBSIM\lib\site-packages\sklearn\linear_model\_coordinate_descent.py:476: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 1451108856.3248856, tolerance: 9680945.629623774
  positive)
2020-04-22 19:16:34:manage:<INFO> success to download from 'food_material_price_predict_model/research/tuned_params.pkl'
C:\BOBSIM\p[...]
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '409290', 'license': 'MIT', 'n_tokens_mistral': 520, 'n_tokens_neox': 441, 'n_words': 93, 'path': 'src/main/python/train_test_volume.ipynb', 'repo_name': 'meowpunch/bobsim-research', 'size': '1365'}