From 8bf371c2a1849f6f0a7c63f0418ef9bd4b336688 Mon Sep 17 00:00:00 2001 From: Angelos Chatzimparmpas Date: Sat, 30 Jan 2021 19:19:33 +0100 Subject: [PATCH] new --- __pycache__/run.cpython-38.pyc | Bin 40260 -> 40263 bytes .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 1 - .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 1 - .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 bytes .../metadata.json | 1 - .../metadata.json | 1 - .../metadata.json | 1 - .../output.pkl | Bin 116 -> 0 bytes .../metadata.json | 2 +- .../output.pkl | Bin 116 -> 116 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delete mode 100644 cachedir/joblib/run/estimator/7b6a78563e5e8041baad07d84d667dd1/metadata.json delete mode 100644 cachedir/joblib/run/estimator/7bb9a6ed4f9c4665154bf105b6bc49d2/metadata.json delete mode 100644 cachedir/joblib/run/estimator/7bb9a6ed4f9c4665154bf105b6bc49d2/output.pkl create mode 100644 cachedir/joblib/run/estimator/ef6bb9df399c46bfde63ecf0478c6582/metadata.json rename cachedir/joblib/run/estimator/{61cc762b5a9bd4586cee079d6c1a7776 => ef6bb9df399c46bfde63ecf0478c6582}/output.pkl (55%) create mode 100644 cachedir/joblib/run/estimator/f4424e7e031a773cea1548224ffc9bc5/metadata.json create mode 100644 cachedir/joblib/run/estimator/f4424e7e031a773cea1548224ffc9bc5/output.pkl diff --git a/__pycache__/run.cpython-38.pyc b/__pycache__/run.cpython-38.pyc index 6cc82a1c30de70117c2f51ac66a9fcf1bce84827..dd15be5207ccac47bf47bc34b974d8d156c2d655 100644 GIT binary patch delta 45 zcmX@Ii|P0-Cf-n9UM>b8I8`Q^Ah?lNOOc;1CqKU+GcP?XH6t@QCv~&4B4Z5zF_#U( delta 42 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estimator(n_estimators, eta, max_depth, subsample, colsample_bytree): # initialize model - print('loopingIris') + print('loopingVehicle') n_estimators = int(n_estimators) max_depth = int(max_depth) model = XGBClassifier(n_estimators=n_estimators, eta=eta, max_depth=max_depth, subsample=subsample, colsample_bytree=colsample_bytree, n_jobs=-1, random_state=RANDOM_SEED, silent=True, verbosity = 0, use_label_encoder=False)