new

cachedir/joblib/run/estimator/07007f7dca9bdfd648d3542e509afb89/metadata.json

@@ -1 +1 @@
-{"duration": 9.244415044784546, "input_args": {"n_estimators": "74.90081706613316", "eta": "0.24281758667148645", "max_depth": "6.444267910404542", "subsample": "0.823173811905026", "colsample_bytree": "0.9458014336081975"}}
+{"duration": 1.3943150043487549, "input_args": {"n_estimators": "74.90081706613316", "eta": "0.24281758667148645", "max_depth": "6.444267910404542", "subsample": "0.823173811905026", "colsample_bytree": "0.9458014336081975"}}

cachedir/joblib/run/estimator/24436eb7944e5f756192f4144586be52/metadata.json

@@ -1 +0,0 @@
-{"duration": 6.655983924865723, "input_args": {"n_estimators": "75.86346086389126", "eta": "0.06372449073826002", "max_depth": "9.472648321000811", "subsample": "0.8945798865585665", "colsample_bytree": "0.9196463484970115"}}

cachedir/joblib/run/estimator/25b4ca0245787f8f861a32778e868901/metadata.json

@@ -0,0 +1 @@
+{"duration": 5.069570064544678, "input_args": {"n_estimators": "166.5474027620548", "eta": "0.050400330952768344", "max_depth": "11.980222535313743", "subsample": "0.9982340891007953", "colsample_bytree": "0.8542949699823068"}}

cachedir/joblib/run/estimator/26eaea169055571f02d589ab35824eec/metadata.json

@@ -1 +0,0 @@
-{"duration": 6.171159029006958, "input_args": {"n_estimators": "91.10980257621819", "eta": "0.1812911976270734", "max_depth": "10.851008286060418", "subsample": "0.9410392159460682", "colsample_bytree": "0.9881736755727641"}}

cachedir/joblib/run/estimator/2d3aa4b9a7a5e05fecd214f13f35c2f6/metadata.json

@@ -1 +1 @@
-{"duration": 1.049651861190796, "input_args": {"n_estimators": "13.819321337554923", "eta": "0.07212312551297988", "max_depth": "7.175897174514871", "subsample": "0.8650660661526529", "colsample_bytree": "0.9843748470046234"}}
+{"duration": 0.3925189971923828, "input_args": {"n_estimators": "13.819321337554923", "eta": "0.07212312551297988", "max_depth": "7.175897174514871", "subsample": "0.8650660661526529", "colsample_bytree": "0.9843748470046234"}}

cachedir/joblib/run/estimator/3e39bc61e5d32214dbfb09418b17d489/metadata.json

@@ -0,0 +1 @@
+{"duration": 2.5982677936553955, "input_args": {"n_estimators": "172.49319703423618", "eta": "0.3", "max_depth": "11.956219561804252", "subsample": "0.9002699436157899", "colsample_bytree": "0.8"}}

cachedir/joblib/run/estimator/501c8577828b16d7edbbaa0c4c50298a/metadata.json

@@ -1 +1 @@
-{"duration": 4.3242270946502686, "input_args": {"n_estimators": "121.73840441842214", "eta": "0.28767857660247903", "max_depth": "10.39196365086843", "subsample": "0.8312037280884873", "colsample_bytree": "0.8749080237694725"}}
+{"duration": 2.650658130645752, "input_args": {"n_estimators": "121.73840441842214", "eta": "0.28767857660247903", "max_depth": "10.39196365086843", "subsample": "0.8312037280884873", "colsample_bytree": "0.8749080237694725"}}

cachedir/joblib/run/estimator/53c192c9764e2921d7ee2543dca13d78/metadata.json

@@ -1 +1 @@
-{"duration": 7.772159814834595, "input_args": {"n_estimators": "182.3174784053625", "eta": "0.17379422752781754", "max_depth": "6.20633112669131", "subsample": "0.8517559963200034", "colsample_bytree": "0.8244076469689559"}}
+{"duration": 2.5463922023773193, "input_args": {"n_estimators": "182.3174784053625", "eta": "0.17379422752781754", "max_depth": "6.20633112669131", "subsample": "0.8517559963200034", "colsample_bytree": "0.8244076469689559"}}

cachedir/joblib/run/estimator/6090fba618ef6aae9c62af2152c10831/metadata.json

@@ -1 +1 @@
-{"duration": 6.074524879455566, "input_args": {"n_estimators": "114.44905352605177", "eta": "0.22831119680574874", "max_depth": "10.564710291701385", "subsample": "0.9541934359909122", "colsample_bytree": "0.8239188491876603"}}
+{"duration": 3.295583963394165, "input_args": {"n_estimators": "114.44905352605177", "eta": "0.22831119680574874", "max_depth": "10.564710291701385", "subsample": "0.9541934359909122", "colsample_bytree": "0.8239188491876603"}}

cachedir/joblib/run/estimator/61afb17f88fffa151324e4d016d0ccee/metadata.json

@@ -1 +0,0 @@
-{"duration": 5.8916871547698975, "input_args": {"n_estimators": "72.11194788979516", "eta": "0.06999909260172242", "max_depth": "11.660767639606618", "subsample": "0.8937069405852791", "colsample_bytree": "0.9970550492754673"}}

cachedir/joblib/run/estimator/65ad99c302a3e6128ffd21fb73ff7858/metadata.json

@@ -1 +1 @@
-{"duration": 2.6692090034484863, "input_args": {"n_estimators": "46.40612658226385", "eta": "0.2924774630404986", "max_depth": "10.99465584480253", "subsample": "0.8363649934414201", "colsample_bytree": "0.8041168988591605"}}
+{"duration": 1.2244741916656494, "input_args": {"n_estimators": "46.40612658226385", "eta": "0.2924774630404986", "max_depth": "10.99465584480253", "subsample": "0.8363649934414201", "colsample_bytree": "0.8041168988591605"}}

cachedir/joblib/run/estimator/878e230e8d668ff8bf9ae658973cf276/metadata.json

@@ -1 +1 @@
-{"duration": 6.29893684387207, "input_args": {"n_estimators": "89.22927863521258", "eta": "0.12606056073988442", "max_depth": "9.148538589793427", "subsample": "0.8582458280396084", "colsample_bytree": "0.8366809019706868"}}
+{"duration": 2.3453609943389893, "input_args": {"n_estimators": "89.22927863521258", "eta": "0.12606056073988442", "max_depth": "9.148538589793427", "subsample": "0.8582458280396084", "colsample_bytree": "0.8366809019706868"}}

cachedir/joblib/run/estimator/8dbc0d7097e6aca21bb30a8dc860f045/metadata.json

@@ -1 +1 @@
-{"duration": 8.566855907440186, "input_args": {"n_estimators": "74.56689870524991", "eta": "0.11783725794347398", "max_depth": "10.972425054911575", "subsample": "0.8561869019374762", "colsample_bytree": "0.8777354579378964"}}
+{"duration": 2.071702003479004, "input_args": {"n_estimators": "74.56689870524991", "eta": "0.11783725794347398", "max_depth": "10.972425054911575", "subsample": "0.8561869019374762", "colsample_bytree": "0.8777354579378964"}}

cachedir/joblib/run/estimator/96ba12b58138896ed090735e777c34ba/metadata.json

@@ -1 +1 @@
-{"duration": 3.1254148483276367, "input_args": {"n_estimators": "17.393878305774606", "eta": "0.20582453170688947", "max_depth": "7.985388149115895", "subsample": "0.8621964643431325", "colsample_bytree": "0.9726206851751187"}}
+{"duration": 0.6976380348205566, "input_args": {"n_estimators": "17.393878305774606", "eta": "0.20582453170688947", "max_depth": "7.985388149115895", "subsample": "0.8621964643431325", "colsample_bytree": "0.9726206851751187"}}

cachedir/joblib/run/estimator/9d6d5c57facf6580e27ecc5ac3a9da74/metadata.json

@@ -1 +1 @@
-{"duration": 8.37943410873413, "input_args": {"n_estimators": "179.4913333333915", "eta": "0.24378320584027863", "max_depth": "11.636993649385134", "subsample": "0.919579995762217", "colsample_bytree": "0.9939169255529117"}}
+{"duration": 3.0700769424438477, "input_args": {"n_estimators": "179.4913333333915", "eta": "0.24378320584027863", "max_depth": "11.636993649385134", "subsample": "0.919579995762217", "colsample_bytree": "0.9939169255529117"}}

cachedir/joblib/run/estimator/b8a9b059b71e375385bcb3affc80aaae/metadata.json

@@ -1 +1 @@
-{"duration": 7.252876043319702, "input_args": {"n_estimators": "138.4254401698706", "eta": "0.1261534422933427", "max_depth": "6.586032684038303", "subsample": "0.8880304987479203", "colsample_bytree": "0.9616794696232922"}}
+{"duration": 2.545977830886841, "input_args": {"n_estimators": "138.4254401698706", "eta": "0.1261534422933427", "max_depth": "6.586032684038303", "subsample": "0.8880304987479203", "colsample_bytree": "0.9616794696232922"}}

cachedir/joblib/run/estimator/bd6da16bc4f265fe52537fa5b2e84845/metadata.json

@@ -1 +1 @@
-{"duration": 7.435333251953125, "input_args": {"n_estimators": "120.52084092809828", "eta": "0.09991844553958994", "max_depth": "9.08540663048167", "subsample": "0.8092900825439996", "colsample_bytree": "0.9570351922786027"}}
+{"duration": 2.421952962875366, "input_args": {"n_estimators": "120.52084092809828", "eta": "0.09991844553958994", "max_depth": "9.08540663048167", "subsample": "0.8092900825439996", "colsample_bytree": "0.9570351922786027"}}

cachedir/joblib/run/estimator/c5ae132fa788a41769fd65f6ea6fc878/metadata.json

@@ -1 +1 @@
-{"duration": 8.807473182678223, "input_args": {"n_estimators": "164.01497854869265", "eta": "0.0996789203835431", "max_depth": "6.033132702741614", "subsample": "0.9413714687695234", "colsample_bytree": "0.9544489538593315"}}
+{"duration": 5.754271984100342, "input_args": {"n_estimators": "164.01497854869265", "eta": "0.0996789203835431", "max_depth": "6.033132702741614", "subsample": "0.9413714687695234", "colsample_bytree": "0.9544489538593315"}}

cachedir/joblib/run/estimator/c78d75f852ea2ac732cd2c4d8cf5e3e3/metadata.json

@@ -1 +1 @@
-{"duration": 11.164775848388672, "input_args": {"n_estimators": "178.00648480238368", "eta": "0.232401544584516", "max_depth": "9.825344828131279", "subsample": "0.8944429850323898", "colsample_bytree": "0.8650366644053494"}}
+{"duration": 3.1356942653656006, "input_args": {"n_estimators": "178.00648480238368", "eta": "0.232401544584516", "max_depth": "9.825344828131279", "subsample": "0.8944429850323898", "colsample_bytree": "0.8650366644053494"}}

cachedir/joblib/run/estimator/d7a4fed50ef206c00c730c9b2e013bcb/metadata.json

@@ -1 +1 @@
-{"duration": 6.8578290939331055, "input_args": {"n_estimators": "111.60850447193953", "eta": "0.12792776902235276", "max_depth": "9.120408127066865", "subsample": "0.8369708911051055", "colsample_bytree": "0.9325044568707964"}}
+{"duration": 2.6464250087738037, "input_args": {"n_estimators": "111.60850447193953", "eta": "0.12792776902235276", "max_depth": "9.120408127066865", "subsample": "0.8369708911051055", "colsample_bytree": "0.9325044568707964"}}

cachedir/joblib/run/estimator/e4ed322c7348967a87d404da78936ef6/metadata.json

@@ -0,0 +1 @@
+{"duration": 2.8645551204681396, "input_args": {"n_estimators": "104.7411734315532", "eta": "0.05", "max_depth": "6.001102182596818", "subsample": "0.8", "colsample_bytree": "1.0"}}

cachedir/joblib/run/estimator/e5b137b59fcad7738516be11e783d76d/metadata.json

@@ -1 +1 @@
-{"duration": 8.713475227355957, "input_args": {"n_estimators": "190.03267976439997", "eta": "0.09263103092182289", "max_depth": "6.390309557911677", "subsample": "0.9931264066149119", "colsample_bytree": "0.9215089703802877"}}
+{"duration": 3.4205880165100098, "input_args": {"n_estimators": "190.03267976439997", "eta": "0.09263103092182289", "max_depth": "6.390309557911677", "subsample": "0.9931264066149119", "colsample_bytree": "0.9215089703802877"}}

cachedir/joblib/run/estimator/e907a73e538f95a05e43901c7239d26f/metadata.json

@@ -1 +1 @@
-{"duration": 4.456164121627808, "input_args": {"n_estimators": "76.44055944226989", "eta": "0.08487346516301046", "max_depth": "7.752867891211309", "subsample": "0.8912139968434072", "colsample_bytree": "0.9223705789444759"}}
+{"duration": 1.844560146331787, "input_args": {"n_estimators": "76.44055944226989", "eta": "0.08487346516301046", "max_depth": "7.752867891211309", "subsample": "0.8912139968434072", "colsample_bytree": "0.9223705789444759"}}

cachedir/joblib/run/estimator/ecc4f427737ec1d8fd0403c51e99091c/metadata.json

@@ -1 +1 @@
-{"duration": 0.946181058883667, "input_args": {"n_estimators": "9.956729715098561", "eta": "0.18068320734549853", "max_depth": "8.565246110151298", "subsample": "0.821578285398661", "colsample_bytree": "0.8987591192728782"}}
+{"duration": 0.32785892486572266, "input_args": {"n_estimators": "9.956729715098561", "eta": "0.18068320734549853", "max_depth": "8.565246110151298", "subsample": "0.821578285398661", "colsample_bytree": "0.8987591192728782"}}

cachedir/joblib/run/estimator/ef6bb9df399c46bfde63ecf0478c6582/metadata.json

@@ -1 +0,0 @@
-{"duration": 7.827345132827759, "input_args": {"n_estimators": "73.50613754427229", "eta": "0.05", "max_depth": "9.336611726304309", "subsample": "1.0", "colsample_bytree": "0.8894830486960281"}}

cachedir/joblib/run/estimator/f1d92e5f2a3bd05ecb2416c00ab93942/metadata.json

@@ -1 +1 @@
-{"duration": 2.4281439781188965, "input_args": {"n_estimators": "19.53737551755531", "eta": "0.08523105624369066", "max_depth": "10.813181884524237", "subsample": "0.9973773873201035", "colsample_bytree": "0.9085392166316497"}}
+{"duration": 0.9457027912139893, "input_args": {"n_estimators": "19.53737551755531", "eta": "0.08523105624369066", "max_depth": "10.813181884524237", "subsample": "0.9973773873201035", "colsample_bytree": "0.9085392166316497"}}

cachedir/joblib/run/estimator/f3a05fd0f610f6b4476dedeade21eb2d/metadata.json

@@ -0,0 +1 @@
+{"duration": 1.8966717720031738, "input_args": {"n_estimators": "69.63591316205535", "eta": "0.3", "max_depth": "6.0", "subsample": "0.8", "colsample_bytree": "0.9778170465164595"}}

cachedir/joblib/run/estimator/f4424e7e031a773cea1548224ffc9bc5/metadata.json

@@ -1 +0,0 @@
-{"duration": 4.726137161254883, "input_args": {"n_estimators": "78.05929830372413", "eta": "0.26819361491123006", "max_depth": "8.416776430272158", "subsample": "0.9282741702875538", "colsample_bytree": "0.8650884194092069"}}

cachedir/joblib/run/estimator/f636511a768ea642182097d47d727cb3/metadata.json

@@ -1 +1 @@
-{"duration": 6.652954816818237, "input_args": {"n_estimators": "122.21742728992572", "eta": "0.06452090304204987", "max_depth": "11.197056874649611", "subsample": "0.941614515559209", "colsample_bytree": "0.8311989040672406"}}
+{"duration": 4.356304883956909, "input_args": {"n_estimators": "122.21742728992572", "eta": "0.06452090304204987", "max_depth": "11.197056874649611", "subsample": "0.941614515559209", "colsample_bytree": "0.8311989040672406"}}

cachedir/joblib/run/estimator/f711c74235d9de3e98bcceeac842befd/metadata.json

@@ -0,0 +1 @@
+{"duration": 4.243398904800415, "input_args": {"n_estimators": "174.53471828158587", "eta": "0.09632267985087588", "max_depth": "6.020831446310865", "subsample": "0.845639293415064", "colsample_bytree": "0.9738813732950363"}}

cachedir/joblib/run/estimator/func_code.py

@@ -1,7 +1,8 @@
-# first line: 524
+# first line: 525
     @memory.cache
     def estimator(n_estimators, eta, max_depth, subsample, colsample_bytree):
         # initialize model
+        print('inside')
         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)

cachedir/joblib/run/estimatorFeatureSelection/0458420fcaa67bddad7fbac56a5ddd15/metadata.json

@@ -1 +0,0 @@
-{"duration": 7.263703107833862, "input_args": {"Data": "     F1  F2  F3  F4  F5  F6  F7  F8  F9\n0     7   8   7   8   9  10  10   1  10\n1     4   5   2   3   4   3   3   1   3\n2     5   8   7  10   5   7   5   4   9\n3     3   7   6   4   4   4   6   1   1\n4     1  10   4   6   4   7   7   2  10\n..   ..  ..  ..  ..  ..  ..  ..  ..  ..\n694   1   1   2   3   1   1   1   1   1\n695   1   3   2   1   1   1   1   1   1\n696   1   3   2   1   2   1   1   2   1\n697   1   3   3   1   1   1   1   1   2\n698   1   2   2   1   1   1   1   1   1\n\n[699 rows x 9 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.21830844624751583,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.218308449,\n              max_delta_step=0, max_depth=7, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=35, n_jobs=12,\n              num_parallel_tree=1, probability=True, random_state=42,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, silent=True,\n              subsample=1, tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}

cachedir/joblib/run/estimatorFeatureSelection/061f896909a89910a77d5c028ec2dbc5/metadata.json

@@ -1 +0,0 @@
-{"duration": 14.65022587776184, "input_args": {"Data": "           F3  F6_b   F3+F6_b  |F3-F6_b|   F3xF6_b   F3/F6_b    F6_b/F3\n0     0.99460     1   1.99460    0.00540   0.99460  0.994600   1.005429\n1     0.99680     1   1.99680    0.00320   0.99680  0.996800   1.003210\n2     0.99690    11  11.99690   10.00310  10.96590  0.090627  11.034206\n3     0.99680     6   6.99680    5.00320   5.98080  0.166133   6.019262\n4     0.99680     3   3.99680    2.00320   2.99040  0.332267   3.009631\n...       ...   ...       ...        ...       ...       ...        ...\n1594  0.99490     2   2.99490    1.00510   1.98980  0.497450   2.010252\n1595  0.99512     2   2.99512    1.00488   1.99024  0.497560   2.009808\n1596  0.99574     3   3.99574    2.00426   2.98722  0.331913   3.012835\n1597  0.99547     3   3.99547    2.00453   2.98641  0.331823   3.013652\n1598  0.99549     9   9.99549    8.00451   8.95941  0.110610   9.040774\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, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/06dd5713420a922c24ec4885229fa897/metadata.json

@@ -1 +0,0 @@
-{"duration": 1.665640115737915, "input_args": {"Data": "     F1_p2    F2_l1p     F1+F2   |F1-F2|     F1xF2     F1/F2      F2/F1\n0     6.25  1.458615  7.708615  4.791385  9.116344  4.284887   0.233378\n1     3.61  1.308333  4.918333  2.301667  4.723081  2.759237   0.362419\n2     4.41  1.386294  5.796294  3.023706  6.113558  3.181143   0.314352\n3     3.24  1.360977  4.600977  1.879023  4.409564  2.380644   0.420054\n4     4.84  1.386294  6.226294  3.453706  6.709665  3.491322   0.286424\n..     ...       ...       ...       ...       ...       ...        ...\n145   0.09  1.386294  1.476294  1.296294  0.124766  0.064921  15.403271\n146   0.04  1.568616  1.608616  1.528616  0.062745  0.025500  39.215398\n147   0.04  1.435085  1.475085  1.395085  0.057403  0.027873  35.877113\n148   0.04  1.547563  1.587563  1.507563  0.061903  0.025847  38.689063\n149   0.04  1.458615  1.498615  1.418615  0.058345  0.027423  36.465376\n\n[150 rows x 7 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.17855860960340292,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.178558603,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=14, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=1, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/06fc90fb00d6d77c094d39a4b81e57a3/metadata.json

@@ -0,0 +1 @@
+{"duration": 47.520893812179565, "input_args": {"Data": "      F1    F2_l1p  F3    F4_p4    F5_l1p     F6_l2    F7_l1p  F8    F9_l1p   F10_l10     F11_p4     F12_p4  F13   F14_l10   F15_l10  F16     F17_p4   F18_l1p\n0    184  5.093750  48  3111696  4.262680  7.622052  2.397895   6  5.176150  1.857332   81450625  639128961   16  2.250420  1.301030  187   47458321  5.940171\n1    158  5.010635  41  4100625  4.290459  7.636625  2.302585   9  5.141664  1.755875   68574961  418161601   14  2.149219  1.278754  189   49787136  5.802118\n2    127  4.976734  41  4477456  4.158883  7.693487  2.302585   6  5.081404  1.799341   74805201  418161601   10  2.201397  1.278754  199   45212176  5.736572\n3    164  4.927254  43  5308416  4.219508  7.658211  2.302585   3  5.093750  1.812913   65610000  454371856    3  2.195900  1.255273  193   18974736  5.641907\n4    112  4.812184  34  8503056  4.174387  7.700440  2.079442   2  4.955827  1.785330   54700816  260144641   14  2.146128  1.230449  200   14776336  5.411646\n..   ...       ...  ..      ...       ...       ...       ...  ..       ...       ...        ...        ...  ...       ...       ...  ...        ...       ...\n841  173  5.017280  43  4100625  4.430817  7.515700  2.079442   4  5.153292  1.740363   52200625  454371856   15  2.089905  1.278754  180   18974736  5.789960\n842  186  5.023881  45  4100625  4.488636  7.531381  3.135494   1  5.231109  1.838849   43046721  466948881   10  2.187521  1.278754  180   21381376  5.817111\n843  119  5.023881  37  3418801  4.189655  7.700440  2.079442   0  5.123964  1.819544   88529281  276922881   16  2.238046  1.278754  201   24010000  5.849325\n844  172  5.093750  47  2560000  4.234107  7.679480  2.079442   9  5.192957  1.845098  100000000  547981281    6  2.267172  1.301030  200   24010000  6.008813\n845  255  5.583496  58   456976  4.454347  7.515700  1.945910   4  5.655992  1.707570  151807041  916636176    8  2.262451  1.462398  181  121550625  6.926577\n\n[846 rows x 18 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8650366644053494,\n              eta=0.232401544584516, gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.23240155,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=178, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=0.8944429850323898, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/07f66c2e206e1b52a9124c8774227ae2/metadata.json

@@ -1 +0,0 @@
-{"duration": 3.801353931427002, "input_args": {"Data": "      F1   F2       F3_em1   F4\n0    2.5  3.3   543.571910  6.0\n1    1.9  2.7   329.299560  5.1\n2    2.1  3.0  1210.967074  5.9\n3    1.8  2.9   543.571910  5.6\n4    2.2  3.0   664.141633  5.8\n..   ...  ...          ...  ...\n145  0.3  3.0   120.510418  1.4\n146  0.2  3.8   163.021907  1.6\n147  0.2  3.2    98.484316  1.4\n148  0.2  3.7   199.336810  1.5\n149  0.2  3.3   147.413159  1.4\n\n[150 rows x 4 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, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/083200d84a0a4d1fbb7b178419d0dc79/metadata.json

@@ -1 +0,0 @@
-{"duration": 18.034281015396118, "input_args": {"Data": "         F1_l2     F2       F3   F4     F5  F6_b   F7    F8     F9_l2   F10   F11   F3xF6_b\n0    -0.621488  0.065  0.99460  7.3   21.0     1  1.2  3.39 -1.089267  15.0  10.0   0.99460\n1    -0.785875  0.073  0.99680  7.8   18.0     1  2.0  3.36 -0.810966   9.0   9.5   0.99680\n2    -1.836501  0.092  0.99690  8.5  103.0    11  1.8  3.30 -0.415037  35.0  10.5  10.96590\n3    -1.395929  0.066  0.99680  8.1   30.0     6  2.1  3.23 -0.454032  13.0   9.7   5.98080\n4    -0.943416  0.085  0.99680  7.5   35.0     3  1.9  3.38 -0.689660  12.0   9.5   2.99040\n...        ...    ...      ...  ...    ...   ...  ...   ...       ...   ...   ...       ...\n1594 -0.736966  0.090  0.99490  6.2   44.0     2  2.0  3.45 -0.785875  32.0  10.5   1.98980\n1595 -0.862496  0.062  0.99512  5.9   51.0     2  2.2  3.52 -0.395929  39.0  11.2   1.99024\n1596 -0.971431  0.076  0.99574  6.3   40.0     3  2.3  3.42 -0.415037  29.0  11.0   2.98722\n1597 -0.632629  0.075  0.99547  5.9   44.0     3  2.0  3.57 -0.494109  32.0  10.2   2.98641\n1598 -1.689660  0.067  0.99549  6.0   42.0     9  3.6  3.39 -0.599462  18.0  11.0   8.95941\n\n[1599 rows x 12 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, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/0ac9d4ad936ae8ef2ecd9a2624cb1f76/metadata.json

@@ -0,0 +1 @@
+{"duration": 73.44196105003357, "input_args": {"Data": "       F4_p4     F17_p4   F18_l1p  F4_p4+F17_p4  F17_p4+F18_l1p  ...  F4_p4/F18_l1p/F17_p4  F17_p4/F18_l1p/F4_p4  F17_p4/F4_p4/F18_l1p  F18_l1p/F4_p4/F17_p4  F18_l1p/F17_p4/F4_p4\n0    3111696   47458321  5.940171      50570017    4.745833e+07  ...              0.011038              2.567534              2.567534          4.022439e-14          4.022439e-14\n1    4100625   49787136  5.802118      53887761    4.978714e+07  ...              0.014195              2.092572              2.092572          2.841969e-14          2.841969e-14\n2    4477456   45212176  5.736572      49689632    4.521218e+07  ...              0.017263              1.760239              1.760239          2.833777e-14          2.833777e-14\n3    5308416   18974736  5.641907      24283152    1.897474e+07  ...              0.049586              0.633556              0.633556          5.601254e-14          5.601254e-14\n4    8503056   14776336  5.411646      23279392    1.477634e+07  ...              0.106336              0.321116              0.321116          4.307126e-14          4.307126e-14\n..       ...        ...       ...           ...             ...  ...                   ...                   ...                   ...                   ...                   ...\n841  4100625   18974736  5.789960      23075361    1.897474e+07  ...              0.037325              0.799190              0.799190          7.441317e-14          7.441317e-14\n842  4100625   21381376  5.817111      25482001    2.138138e+07  ...              0.032969              0.896351              0.896351          6.634706e-14          6.634706e-14\n843  3418801   24010000  5.849325      27428801    2.401001e+07  ...              0.024343              1.200639              1.200639          7.125900e-14          7.125900e-14\n844  2560000   24010000  6.008813      26570000    2.401001e+07  ...              0.017744              1.560858              1.560858          9.775896e-14          9.775896e-14\n845   456976  121550625  6.926577     122007601    1.215506e+08  ...              0.000543             38.401230             38.401230          1.247005e-13          1.247005e-13\n\n[846 rows x 27 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8650366644053494,\n              eta=0.232401544584516, gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.23240155,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=178, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=0.8944429850323898, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/0b5341d3e1474cd2b4d28e1033a5e75b/metadata.json

@@ -1 +0,0 @@
-{"duration": 15.683412075042725, "input_args": {"Data": "     F1  F2   F3  F4   F5  F6   F7  F8   F9  F10  F11  F12  F13\n0     1   0  145   0  150  63  233   1  2.3    0    3    0    1\n1     0   0  130   0  187  37  250   1  3.5    1    2    0    2\n2     0   2  130   0  172  41  204   0  1.4    0    1    0    2\n3     0   2  120   0  178  56  236   1  0.8    1    1    0    2\n4     0   2  120   1  163  57  354   0  0.6    1    0    0    2\n..   ..  ..  ...  ..  ...  ..  ...  ..  ...  ...  ...  ...  ...\n298   0   1  140   1  123  57  241   0  0.2    1    0    0    3\n299   0   1  110   0  132  45  264   1  1.2    1    3    0    3\n300   1   1  144   0  141  68  193   1  3.4    1    0    2    3\n301   0   1  130   1  115  57  131   1  1.2    1    0    1    3\n302   0   1  130   0  174  57  236   0  0.0    0    1    1    2\n\n[303 rows x 13 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.1436350297118406,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.143635035,\n              max_delta_step=0, max_depth=11, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=196, n_jobs=12,\n              num_parallel_tree=1, probability=True, random_state=42,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, silent=True,\n              subsample=1, tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}

cachedir/joblib/run/estimatorFeatureSelection/0ef4d1cbb067b8b5550bd232e020b562/metadata.json

@@ -0,0 +1 @@
+{"duration": 45.27411508560181, "input_args": {"Data": "      F1    F2_l1p  F3    F4_p4  F5   F6    F7_l1p  F8   F9  F10  F11  F12  F13  F14   F15_l10  F16  F17   F18_l1p\n0    184  5.093750  48  3111696  70  197  2.397895   6  176   72   95  159   16  178  1.301030  187   83  5.940171\n1    158  5.010635  41  4100625  72  199  2.302585   9  170   57   91  143   14  141  1.278754  189   84  5.802118\n2    127  4.976734  41  4477456  63  207  2.302585   6  160   63   93  143   10  159  1.278754  199   82  5.736572\n3    164  4.927254  43  5308416  67  202  2.302585   3  162   65   90  146    3  157  1.255273  193   66  5.641907\n4    112  4.812184  34  8503056  64  208  2.079442   2  141   61   86  127   14  140  1.230449  200   62  5.411646\n..   ...       ...  ..      ...  ..  ...       ...  ..  ...  ...  ...  ...  ...  ...       ...  ...  ...       ...\n841  173  5.017280  43  4100625  83  183  2.079442   4  172   55   85  146   15  123  1.278754  180   66  5.789960\n842  186  5.023881  45  4100625  88  185  3.135494   1  186   69   81  147   10  154  1.278754  180   68  5.817111\n843  119  5.023881  37  3418801  65  208  2.079442   0  167   66   97  129   16  173  1.278754  201   70  5.849325\n844  172  5.093750  47  2560000  68  205  2.079442   9  179   70  100  153    6  185  1.301030  200   70  6.008813\n845  255  5.583496  58   456976  85  183  1.945910   4  285   51  111  174    8  183  1.462398  181  105  6.926577\n\n[846 rows x 18 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8650366644053494,\n              eta=0.232401544584516, gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.23240155,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=178, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=0.8944429850323898, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/10a4c33e4cbdc2169a509ee22bd63ae5/metadata.json

@@ -1 +0,0 @@
-{"duration": 15.355908155441284, "input_args": {"Data": "         F1_l2     F2       F3   F4     F5  F6_b   F7    F8     F9_l2   F10   F11\n0    -0.621488  0.065  0.99460  7.3   21.0     1  1.2  3.39 -1.089267  15.0  10.0\n1    -0.785875  0.073  0.99680  7.8   18.0     1  2.0  3.36 -0.810966   9.0   9.5\n2    -1.836501  0.092  0.99690  8.5  103.0    11  1.8  3.30 -0.415037  35.0  10.5\n3    -1.395929  0.066  0.99680  8.1   30.0     6  2.1  3.23 -0.454032  13.0   9.7\n4    -0.943416  0.085  0.99680  7.5   35.0     3  1.9  3.38 -0.689660  12.0   9.5\n...        ...    ...      ...  ...    ...   ...  ...   ...       ...   ...   ...\n1594 -0.736966  0.090  0.99490  6.2   44.0     2  2.0  3.45 -0.785875  32.0  10.5\n1595 -0.862496  0.062  0.99512  5.9   51.0     2  2.2  3.52 -0.395929  39.0  11.2\n1596 -0.971431  0.076  0.99574  6.3   40.0     3  2.3  3.42 -0.415037  29.0  11.0\n1597 -0.632629  0.075  0.99547  5.9   44.0     3  2.0  3.57 -0.494109  32.0  10.2\n1598 -1.689660  0.067  0.99549  6.0   42.0     9  3.6  3.39 -0.599462  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, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/1276da95d3d21f94d4712976522769ea/metadata.json

@@ -1 +0,0 @@
-{"duration": 2.59732985496521, "input_args": {"Data": "       F1_l10   F3   F4\n0    0.397940  6.3  6.0\n1    0.278754  5.8  5.1\n2    0.322219  7.1  5.9\n3    0.255273  6.3  5.6\n4    0.342423  6.5  5.8\n..        ...  ...  ...\n145 -0.522879  4.8  1.4\n146 -0.698970  5.1  1.6\n147 -0.698970  4.6  1.4\n148 -0.698970  5.3  1.5\n149 -0.698970  5.0  1.4\n\n[150 rows x 3 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.17855860960340292,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.178558603,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=14, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=1, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/155fb13ac5302f6e83e8dee4e6e50e10/metadata.json

@@ -1 +0,0 @@
-{"duration": 1.2182409763336182, "input_args": {"Data": "      F1   F2   F3     F4_l2\n0    2.5  3.3  6.3  2.584963\n1    1.9  2.7  5.8  2.350497\n2    2.1  3.0  7.1  2.560715\n3    1.8  2.9  6.3  2.485427\n4    2.2  3.0  6.5  2.536053\n..   ...  ...  ...       ...\n145  0.3  3.0  4.8  0.485427\n146  0.2  3.8  5.1  0.678072\n147  0.2  3.2  4.6  0.485427\n148  0.2  3.7  5.3  0.584963\n149  0.2  3.3  5.0  0.485427\n\n[150 rows x 4 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.17855860960340292,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.178558603,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=14, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=1, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/15b0b603c741872ef31ad44a4ac4bc66/metadata.json

@@ -1 +0,0 @@
-{"duration": 1.2176530361175537, "input_args": {"Data": "     F1_p2    F2_l1p       F3_em1     F4_l2\n0     6.25  1.458615   543.571910  2.584963\n1     3.61  1.308333   329.299560  2.350497\n2     4.41  1.386294  1210.967074  2.560715\n3     3.24  1.360977   543.571910  2.485427\n4     4.84  1.386294   664.141633  2.536053\n..     ...       ...          ...       ...\n145   0.09  1.386294   120.510418  0.485427\n146   0.04  1.568616   163.021907  0.678072\n147   0.04  1.435085    98.484316  0.485427\n148   0.04  1.547563   199.336810  0.584963\n149   0.04  1.458615   147.413159  0.485427\n\n[150 rows x 4 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.17855860960340292,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.178558603,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=14, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=1, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/1a6b490454e7bf1073feef75f2d33016/metadata.json

@@ -1 +0,0 @@
-{"duration": 6.107879161834717, "input_args": {"Data": "     F1  F2  F3  F4  F5  F6  F7  F9\n0     7   8   7   8   9  10  10  10\n1     4   5   2   3   4   3   3   3\n2     5   8   7  10   5   7   5   9\n3     3   7   6   4   4   4   6   1\n4     1  10   4   6   4   7   7  10\n..   ..  ..  ..  ..  ..  ..  ..  ..\n694   1   1   2   3   1   1   1   1\n695   1   3   2   1   1   1   1   1\n696   1   3   2   1   2   1   1   1\n697   1   3   3   1   1   1   1   2\n698   1   2   2   1   1   1   1   1\n\n[699 rows x 8 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.0989957156047863,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.0989957154,\n              max_delta_step=0, max_depth=6, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=68, n_jobs=12,\n              num_parallel_tree=1, probability=True, random_state=42,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, silent=True,\n              subsample=1, tree_method='exact', use_label_encoder=False,\n              validate_parameters=1, verbosity=0)"}}

cachedir/joblib/run/estimatorFeatureSelection/1d757a543a7ff69019ec13d167f09684/metadata.json

@@ -1 +0,0 @@
-{"duration": 7.925899028778076, "input_args": {"Data": "     F1_p2    F2_l1p       F3_em1     F1+F2        F2+F3        F1+F3     F1+F2+F3   |F1-F2|  ...     F1/F3        F3/F1  F1/F2/F3  F1/F3/F2  F2/F3/F1  F2/F1/F3     F3/F1/F2     F3/F2/F1\n0     6.25  1.458615   543.571910  7.708615   545.030525   549.821910   551.280525  4.791385  ...  0.011498    86.971506  0.007883  0.007883  0.000429  0.000429    59.626087    59.626087\n1     3.61  1.308333   329.299560  4.918333   330.607893   332.909560   334.217893  2.301667  ...  0.010963    91.218715  0.008379  0.008379  0.001101  0.001101    69.721338    69.721338\n2     4.41  1.386294  1210.967074  5.796294  1212.353369  1215.377074  1216.763369  3.023706  ...  0.003642   274.595709  0.002627  0.002627  0.000260  0.000260   198.078933   198.078933\n3     3.24  1.360977   543.571910  4.600977   544.932887   546.811910   548.172887  1.879023  ...  0.005961   167.769108  0.004380  0.004380  0.000773  0.000773   123.271123   123.271123\n4     4.84  1.386294   664.141633  6.226294   665.527927   668.981633   670.367927  3.453706  ...  0.007288   137.219346  0.005257  0.005257  0.000431  0.000431    98.982835    98.982835\n..     ...       ...          ...       ...          ...          ...          ...       ...  ...       ...          ...       ...       ...       ...       ...          ...          ...\n145   0.09  1.386294   120.510418  1.476294   121.896712   120.600418   121.986712  1.296294  ...  0.000747  1339.004639  0.000539  0.000539  0.127817  0.127817   965.887676   965.887676\n146   0.04  1.568616   163.021907  1.608616   164.590523   163.061907   164.630523  1.528616  ...  0.000245  4075.547682  0.000156  0.000156  0.240553  0.240553  2598.180750  2598.180750\n147   0.04  1.435085    98.484316  1.475085    99.919400    98.524316    99.959400  1.395085  ...  0.000406  2462.107891  0.000283  0.000283  0.364293  0.364293  1715.653571  1715.653571\n148   0.04  1.547563   199.336810  1.587563   200.884372   199.376810   200.924372  1.507563  ...  0.000201  4983.420249  0.000130  0.000130  0.194089  0.194089  3220.173803  3220.173803\n149   0.04  1.458615   147.413159  1.498615   148.871774   147.453159   148.911774  1.418615  ...  0.000271  3685.328978  0.000186  0.000186  0.247369  0.247369  2526.594694  2526.594694\n\n[150 rows x 27 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, eta=0.17855860960340292,\n              gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.178558603,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=14, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=1, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/262729b93d27e5fde35bf74327233777/metadata.json

@@ -0,0 +1 @@
+{"duration": 45.19109106063843, "input_args": {"Data": "      F1    F2_l1p  F3    F4_p4    F5_l1p     F6_l2    F7_l1p  F8    F9_l1p  F10     F11_p4  F12  F13   F14_l10   F15_l10  F16  F17   F18_l1p\n0    184  5.093750  48  3111696  4.262680  7.622052  2.397895   6  5.176150   72   81450625  159   16  2.250420  1.301030  187   83  5.940171\n1    158  5.010635  41  4100625  4.290459  7.636625  2.302585   9  5.141664   57   68574961  143   14  2.149219  1.278754  189   84  5.802118\n2    127  4.976734  41  4477456  4.158883  7.693487  2.302585   6  5.081404   63   74805201  143   10  2.201397  1.278754  199   82  5.736572\n3    164  4.927254  43  5308416  4.219508  7.658211  2.302585   3  5.093750   65   65610000  146    3  2.195900  1.255273  193   66  5.641907\n4    112  4.812184  34  8503056  4.174387  7.700440  2.079442   2  4.955827   61   54700816  127   14  2.146128  1.230449  200   62  5.411646\n..   ...       ...  ..      ...       ...       ...       ...  ..       ...  ...        ...  ...  ...       ...       ...  ...  ...       ...\n841  173  5.017280  43  4100625  4.430817  7.515700  2.079442   4  5.153292   55   52200625  146   15  2.089905  1.278754  180   66  5.789960\n842  186  5.023881  45  4100625  4.488636  7.531381  3.135494   1  5.231109   69   43046721  147   10  2.187521  1.278754  180   68  5.817111\n843  119  5.023881  37  3418801  4.189655  7.700440  2.079442   0  5.123964   66   88529281  129   16  2.238046  1.278754  201   70  5.849325\n844  172  5.093750  47  2560000  4.234107  7.679480  2.079442   9  5.192957   70  100000000  153    6  2.267172  1.301030  200   70  6.008813\n845  255  5.583496  58   456976  4.454347  7.515700  1.945910   4  5.655992   51  151807041  174    8  2.262451  1.462398  181  105  6.926577\n\n[846 rows x 18 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8650366644053494,\n              eta=0.232401544584516, gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.23240155,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=178, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=0.8944429850323898, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/288e001fe3bc6466bca37ab31dbda41f/metadata.json

@@ -0,0 +1 @@
+{"duration": 52.61242914199829, "input_args": {"Data": "      F1    F2_l1p  F3    F4_p4    F5_l1p     F6_l2    F7_l1p  F8    F9_l1p   F10_l10     F11_p4     F12_p4  F13   F14_l10   F15_l10  F16     F17_p4   F18_l1p  F4_p4/F15_l10/F18_l1p\n0    184  5.093750  48  3111696  4.262680  7.622052  2.397895   6  5.176150  1.857332   81450625  639128961   16  2.250420  1.301030  187   47458321  5.940171           4.026344e+05\n1    158  5.010635  41  4100625  4.290459  7.636625  2.302585   9  5.141664  1.755875   68574961  418161601   14  2.149219  1.278754  189   49787136  5.802118           5.526836e+05\n2    127  4.976734  41  4477456  4.158883  7.693487  2.302585   6  5.081404  1.799341   74805201  418161601   10  2.201397  1.278754  199   45212176  5.736572           6.103683e+05\n3    164  4.927254  43  5308416  4.219508  7.658211  2.302585   3  5.093750  1.812913   65610000  454371856    3  2.195900  1.255273  193   18974736  5.641907           7.495507e+05\n4    112  4.812184  34  8503056  4.174387  7.700440  2.079442   2  4.955827  1.785330   54700816  260144641   14  2.146128  1.230449  200   14776336  5.411646           1.276974e+06\n..   ...       ...  ..      ...       ...       ...       ...  ..       ...       ...        ...        ...  ...       ...       ...  ...        ...       ...                    ...\n841  173  5.017280  43  4100625  4.430817  7.515700  2.079442   4  5.153292  1.740363   52200625  454371856   15  2.089905  1.278754  180   18974736  5.789960           5.538442e+05\n842  186  5.023881  45  4100625  4.488636  7.531381  3.135494   1  5.231109  1.838849   43046721  466948881   10  2.187521  1.278754  180   21381376  5.817111           5.512592e+05\n843  119  5.023881  37  3418801  4.189655  7.700440  2.079442   0  5.123964  1.819544   88529281  276922881   16  2.238046  1.278754  201   24010000  5.849325           4.570684e+05\n844  172  5.093750  47  2560000  4.234107  7.679480  2.079442   9  5.192957  1.845098  100000000  547981281    6  2.267172  1.301030  200   24010000  6.008813           3.274643e+05\n845  255  5.583496  58   456976  4.454347  7.515700  1.945910   4  5.655992  1.707570  151807041  916636176    8  2.262451  1.462398  181  121550625  6.926577           4.511377e+04\n\n[846 rows x 19 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8650366644053494,\n              eta=0.232401544584516, gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.23240155,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=178, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=0.8944429850323898, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/2bc932fe8a1e9f104d58df4b3b8a39ce/metadata.json

@@ -1 +0,0 @@
-{"duration": 21.434664964675903, "input_args": {"Data": "         F1     F2       F3   F4     F5  F6_b   F7    F8    F9   F10   F11   F3/F6_b\n0     0.650  0.065  0.99460  7.3   21.0     1  1.2  3.39  0.47  15.0  10.0  0.994600\n1     0.580  0.073  0.99680  7.8   18.0     1  2.0  3.36  0.57   9.0   9.5  0.996800\n2     0.280  0.092  0.99690  8.5  103.0    11  1.8  3.30  0.75  35.0  10.5  0.090627\n3     0.380  0.066  0.99680  8.1   30.0     6  2.1  3.23  0.73  13.0   9.7  0.166133\n4     0.520  0.085  0.99680  7.5   35.0     3  1.9  3.38  0.62  12.0   9.5  0.332267\n...     ...    ...      ...  ...    ...   ...  ...   ...   ...   ...   ...       ...\n1594  0.600  0.090  0.99490  6.2   44.0     2  2.0  3.45  0.58  32.0  10.5  0.497450\n1595  0.550  0.062  0.99512  5.9   51.0     2  2.2  3.52  0.76  39.0  11.2  0.497560\n1596  0.510  0.076  0.99574  6.3   40.0     3  2.3  3.42  0.75  29.0  11.0  0.331913\n1597  0.645  0.075  0.99547  5.9   44.0     3  2.0  3.57  0.71  32.0  10.2  0.331823\n1598  0.310  0.067  0.99549  6.0   42.0     9  3.6  3.39  0.66  18.0  11.0  0.110610\n\n[1599 rows x 12 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, ...)"}}

cachedir/joblib/run/estimatorFeatureSelection/2e53de4c7e8abc9521a9c49e70c59bc4/metadata.json

@@ -0,0 +1 @@
+{"duration": 45.19006395339966, "input_args": {"Data": "      F1   F2  F3    F4_p4  F5   F6  F7  F8   F9  F10  F11  F12  F13  F14  F15  F16  F17   F18\n0    184  162  48  3111696  70  197  10   6  176   72   95  159   16  178   20  187   83   379\n1    158  149  41  4100625  72  199   9   9  170   57   91  143   14  141   19  189   84   330\n2    127  144  41  4477456  63  207   9   6  160   63   93  143   10  159   19  199   82   309\n3    164  137  43  5308416  67  202   9   3  162   65   90  146    3  157   18  193   66   281\n4    112  122  34  8503056  64  208   7   2  141   61   86  127   14  140   17  200   62   223\n..   ...  ...  ..      ...  ..  ...  ..  ..  ...  ...  ...  ...  ...  ...  ...  ...  ...   ...\n841  173  150  43  4100625  83  183   7   4  172   55   85  146   15  123   19  180   66   326\n842  186  151  45  4100625  88  185  22   1  186   69   81  147   10  154   19  180   68   335\n843  119  151  37  3418801  65  208   7   0  167   66   97  129   16  173   19  201   70   346\n844  172  162  47  2560000  68  205   7   9  179   70  100  153    6  185   20  200   70   406\n845  255  265  58   456976  85  183   6   4  285   51  111  174    8  183   29  181  105  1018\n\n[846 rows x 18 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=0.8650366644053494,\n              eta=0.232401544584516, gamma=0, gpu_id=-1, importance_type='gain',\n              interaction_constraints='', learning_rate=0.23240155,\n              max_delta_step=0, max_depth=9, min_child_weight=1, missing=nan,\n              monotone_constraints='()', n_estimators=178, n_jobs=12,\n              num_parallel_tree=1, objective='multi:softprob', probability=True,\n              random_state=42, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,\n              silent=True, subsample=0.8944429850323898, tree_method='exact',\n              use_label_encoder=False, validate_parameters=1, ...)"}}