FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches
https://doi.org/10.1109/TVCG.2022.3141040
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
1 lines
1.7 KiB
1 lines
1.7 KiB
{"duration": 34.247978925704956, "input_args": {"Data": " F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11\n0 0.650 0.065 0.99460 7.3 21.0 0.00 1.2 3.39 0.47 15.0 10.0\n1 0.580 0.073 0.99680 7.8 18.0 0.02 2.0 3.36 0.57 9.0 9.5\n2 0.280 0.092 0.99690 8.5 103.0 0.56 1.8 3.30 0.75 35.0 10.5\n3 0.380 0.066 0.99680 8.1 30.0 0.28 2.1 3.23 0.73 13.0 9.7\n4 0.520 0.085 0.99680 7.5 35.0 0.16 1.9 3.38 0.62 12.0 9.5\n... ... ... ... ... ... ... ... ... ... ... ...\n1594 0.600 0.090 0.99490 6.2 44.0 0.08 2.0 3.45 0.58 32.0 10.5\n1595 0.550 0.062 0.99512 5.9 51.0 0.10 2.2 3.52 0.76 39.0 11.2\n1596 0.510 0.076 0.99574 6.3 40.0 0.13 2.3 3.42 0.75 29.0 11.0\n1597 0.645 0.075 0.99547 5.9 44.0 0.12 2.0 3.57 0.71 32.0 10.2\n1598 0.310 0.067 0.99549 6.0 42.0 0.47 3.6 3.39 0.66 18.0 11.0\n\n[1599 rows x 11 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.9223705789444759,\n eta=0.08487346516301046, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.0848734677, max_delta_step=0, max_depth=7,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=76, n_jobs=12, num_parallel_tree=1,\n objective='multi:softprob', probability=True, random_state=42,\n reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n subsample=0.8912139968434072, tree_method='exact',\n use_label_encoder=False, validate_parameters=1, ...)"}} |