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a/cachedir/joblib/run/estimator/f711c74235d9de3e98bcceeac842befd/metadata.json +++ /dev/null @@ -1 +0,0 @@ -{"duration": 4.243398904800415, "input_args": {"n_estimators": "174.53471828158587", "eta": "0.09632267985087588", "max_depth": "6.020831446310865", "subsample": "0.845639293415064", "colsample_bytree": "0.9738813732950363"}} \ No newline at end of file diff --git a/cachedir/joblib/run/estimator/f711c74235d9de3e98bcceeac842befd/output.pkl b/cachedir/joblib/run/estimator/f711c74235d9de3e98bcceeac842befd/output.pkl deleted file mode 100644 index e67632d..0000000 Binary files a/cachedir/joblib/run/estimator/f711c74235d9de3e98bcceeac842befd/output.pkl and /dev/null differ diff --git a/cachedir/joblib/run/estimator/func_code.py b/cachedir/joblib/run/estimator/func_code.py index 9f95592..f2adce1 100644 --- a/cachedir/joblib/run/estimator/func_code.py +++ b/cachedir/joblib/run/estimator/func_code.py @@ -2,7 +2,7 @@ @memory.cache def estimator(n_estimators, eta, max_depth, subsample, colsample_bytree): # initialize model - print('inside') + print('loopingIris') 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) diff --git a/cachedir/joblib/run/estimatorFeatureSelection/1c4353e412fa2d5faad7cd95e060ac0b/output.pkl b/cachedir/joblib/run/estimatorFeatureSelection/1c4353e412fa2d5faad7cd95e060ac0b/output.pkl new file mode 100644 index 0000000..578d2e7 Binary files /dev/null and b/cachedir/joblib/run/estimatorFeatureSelection/1c4353e412fa2d5faad7cd95e060ac0b/output.pkl differ diff --git a/cachedir/joblib/run/estimatorFeatureSelection/1edf0aab1322bad6d8bc1faf9d99ec87/metadata.json b/cachedir/joblib/run/estimatorFeatureSelection/1edf0aab1322bad6d8bc1faf9d99ec87/metadata.json new file mode 100644 index 0000000..b5c245b --- /dev/null +++ b/cachedir/joblib/run/estimatorFeatureSelection/1edf0aab1322bad6d8bc1faf9d99ec87/metadata.json @@ -0,0 +1 @@ +{"duration": 21.04797101020813, "input_args": {"Data": " F1_l2 F6_b F1_l2+F6_b |F1_l2-F6_b| F1_l2xF6_b F1_l2/F6_b F6_b/F1_l2\n0 -0.621488 1 0.378512 1.621488 -0.621488 -0.621488 -1.609041\n1 -0.785875 1 0.214125 1.785875 -0.785875 -0.785875 -1.272467\n2 -1.836501 11 9.163499 12.836501 -20.201514 -0.166955 -5.989650\n3 -1.395929 6 4.604071 7.395929 -8.375572 -0.232655 -4.298214\n4 -0.943416 3 2.056584 3.943416 -2.830249 -0.314472 -3.179932\n... ... ... ... ... ... ... ...\n1594 -0.736966 2 1.263034 2.736966 -1.473931 -0.368483 -2.713831\n1595 -0.862496 2 1.137504 2.862496 -1.724993 -0.431248 -2.318850\n1596 -0.971431 3 2.028569 3.971431 -2.914293 -0.323810 -3.088228\n1597 -0.632629 3 2.367371 3.632629 -1.897887 -0.210876 -4.742116\n1598 -1.689660 9 7.310340 10.689660 -15.206939 -0.187740 -5.326516\n\n[1599 rows x 7 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, ...)"}} \ No newline at end of file diff --git a/cachedir/joblib/run/estimatorFeatureSelection/2956fe3fc2ead99c0e75e9a3188d9e47/output.pkl b/cachedir/joblib/run/estimatorFeatureSelection/2956fe3fc2ead99c0e75e9a3188d9e47/output.pkl new file mode 100644 index 0000000..c6b556a Binary files /dev/null and b/cachedir/joblib/run/estimatorFeatureSelection/2956fe3fc2ead99c0e75e9a3188d9e47/output.pkl differ diff --git a/cachedir/joblib/run/estimatorFeatureSelection/2a5cb0dc93c4d28175bea04aba90196b/output.pkl b/cachedir/joblib/run/estimatorFeatureSelection/2a5cb0dc93c4d28175bea04aba90196b/output.pkl new file mode 100644 index 0000000..6b7e1fd Binary files /dev/null and b/cachedir/joblib/run/estimatorFeatureSelection/2a5cb0dc93c4d28175bea04aba90196b/output.pkl differ diff --git a/cachedir/joblib/run/estimatorFeatureSelection/5c6d9ec9ebd0c96ad37bcece2a7b1ab1/metadata.json b/cachedir/joblib/run/estimatorFeatureSelection/5c6d9ec9ebd0c96ad37bcece2a7b1ab1/metadata.json new file mode 100644 index 0000000..d06314e --- /dev/null +++ b/cachedir/joblib/run/estimatorFeatureSelection/5c6d9ec9ebd0c96ad37bcece2a7b1ab1/metadata.json @@ -0,0 +1 @@ +{"duration": 13.459782838821411, "input_args": {"Data": " F1_l2 F2 F3 F4 F5 F6 F7 F8 F9_l10 F10 F11\n0 -0.621488 0.065 0.99460 7.3 21.0 0.00 1.2 3.39 -0.327902 15.0 10.0\n1 -0.785875 0.073 0.99680 7.8 18.0 0.02 2.0 3.36 -0.244125 9.0 9.5\n2 -1.836501 0.092 0.99690 8.5 103.0 0.56 1.8 3.30 -0.124939 35.0 10.5\n3 -1.395929 0.066 0.99680 8.1 30.0 0.28 2.1 3.23 -0.136677 13.0 9.7\n4 -0.943416 0.085 0.99680 7.5 35.0 0.16 1.9 3.38 -0.207608 12.0 9.5\n... ... ... ... ... ... ... ... ... ... ... ...\n1594 -0.736966 0.090 0.99490 6.2 44.0 0.08 2.0 3.45 -0.236572 32.0 10.5\n1595 -0.862496 0.062 0.99512 5.9 51.0 0.10 2.2 3.52 -0.119186 39.0 11.2\n1596 -0.971431 0.076 0.99574 6.3 40.0 0.13 2.3 3.42 -0.124939 29.0 11.0\n1597 -0.632629 0.075 0.99547 5.9 44.0 0.12 2.0 3.57 -0.148742 32.0 10.2\n1598 -1.689660 0.067 0.99549 6.0 42.0 0.47 3.6 3.39 -0.180456 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, ...)"}} \ No newline at end of file diff --git a/cachedir/joblib/run/estimatorFeatureSelection/5fa740243b273457bc3baef8701c08b7/metadata.json b/cachedir/joblib/run/estimatorFeatureSelection/5fa740243b273457bc3baef8701c08b7/metadata.json new file mode 100644 index 0000000..0e962a3 --- /dev/null +++ b/cachedir/joblib/run/estimatorFeatureSelection/5fa740243b273457bc3baef8701c08b7/metadata.json @@ -0,0 +1 @@ +{"duration": 13.591701030731201, "input_args": {"Data": " F1_l2 F2 F3 F4 F5 F6_b F7 F8 F9_l10 F10 F11\n0 -0.621488 0.065 0.99460 7.3 21.0 1 1.2 3.39 -0.327902 15.0 10.0\n1 -0.785875 0.073 0.99680 7.8 18.0 1 2.0 3.36 -0.244125 9.0 9.5\n2 -1.836501 0.092 0.99690 8.5 103.0 11 1.8 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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, ...)"}} \ No newline at end of file diff --git a/cachedir/joblib/run/estimatorFeatureSelection/6cb9aa4d3e4f65304fcd4f4b64757ac2/output.pkl b/cachedir/joblib/run/estimatorFeatureSelection/6cb9aa4d3e4f65304fcd4f4b64757ac2/output.pkl new file mode 100644 index 0000000..62cfb34 Binary files /dev/null and b/cachedir/joblib/run/estimatorFeatureSelection/6cb9aa4d3e4f65304fcd4f4b64757ac2/output.pkl differ diff --git a/cachedir/joblib/run/estimatorFeatureSelection/72ac4adfa3e5cbdd57bcba63418bbace/output.pkl b/cachedir/joblib/run/estimatorFeatureSelection/72ac4adfa3e5cbdd57bcba63418bbace/output.pkl new file mode 100644 index 0000000..43a849b Binary files /dev/null and b/cachedir/joblib/run/estimatorFeatureSelection/72ac4adfa3e5cbdd57bcba63418bbace/output.pkl differ 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Process Tracker and Predictive Results + Process Tracker and Predictive Results @@ -149,6 +149,7 @@ export default Vue.extend({ DataResults: '', keyNow: 1, instancesImportance: '', + //RetrieveValueFile: 'VehicleC', // this is for the default data set RetrieveValueFile: 'VehicleC', // this is for the default data set SelectedFeaturesPerClassifier: '', FinalResults: 0, @@ -476,7 +477,7 @@ export default Vue.extend({ EventBus.$emit('SlidersCall') this.keySlider = false } - //EventBus.$emit('ConfirmDataSet') // REMOVE THAT! + EventBus.$emit('ConfirmDataSet') // REMOVE THAT! } else { EventBus.$emit('dataSpace', this.correlResul) EventBus.$emit('quad', this.correlResul) @@ -862,7 +863,7 @@ body { top: 0px; bottom: 0px; margin-top: -4px !important; - overflow: hidden !important; // remove scrolling + //overflow: hidden !important; // remove scrolling } .modal-backdrop { diff --git a/run.py b/run.py index 8d0c943..e9e3269 100644 --- a/run.py +++ b/run.py @@ -525,7 +525,7 @@ def create_global_function(): @memory.cache def estimator(n_estimators, eta, max_depth, subsample, colsample_bytree): # initialize model - print('inside') + 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)