From 11889658757b4fc58cdfb70639180d7c71b6ad0d Mon Sep 17 00:00:00 2001
From: fakenewssyria <fakenewssyria@gmail.com>
Date: Mon, 7 Jun 2021 13:04:58 +0300
Subject: [PATCH] added runner file for xgboost generating risk df with 0 being
 positive class

---
 .../error_metrics/testing_errors.csv          |   2 +
 .../error_metrics/validation_errors.csv       |   2 +
 .../error_metrics/winning_hyperparameters.csv |   2 +
 .../output_vector/xg_boost_test.csv           | 162 ++++++++++++++++++
 .../trained_models/risk_df_xg_boost.csv       | 162 ++++++++++++++++++
 .../trained_models/xg_boost.pickle            | Bin 0 -> 63161 bytes
 .../Shallow/Experiment1/xgboost_0poslabel.py  |  32 ++++
 7 files changed, 362 insertions(+)
 create mode 100644 Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/testing_errors.csv
 create mode 100644 Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/validation_errors.csv
 create mode 100644 Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/winning_hyperparameters.csv
 create mode 100644 Experiments/Shallow/Experiment1/output_xgboost_poslabel0/output_vector/xg_boost_test.csv
 create mode 100644 Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/risk_df_xg_boost.csv
 create mode 100644 Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/xg_boost.pickle
 create mode 100644 Experiments/Shallow/Experiment1/xgboost_0poslabel.py

diff --git a/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/testing_errors.csv b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/testing_errors.csv
new file mode 100644
index 0000000..44a0750
--- /dev/null
+++ b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/testing_errors.csv
@@ -0,0 +1,2 @@
+model,accuracy,precision,recall,f1,auc,TN,FP,FN,TP
+xg_boost,0.88199,0.84444,0.93827,0.88889,0.88164,66,14,5,76
diff --git a/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/validation_errors.csv b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/validation_errors.csv
new file mode 100644
index 0000000..031cd71
--- /dev/null
+++ b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/validation_errors.csv
@@ -0,0 +1,2 @@
+model,accuracy,precision,recall,f1,auc
+xg_boost,0.88316,0.87112,0.92543,0.89638,0.87911
diff --git a/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/winning_hyperparameters.csv b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/winning_hyperparameters.csv
new file mode 100644
index 0000000..5cf61d3
--- /dev/null
+++ b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/error_metrics/winning_hyperparameters.csv
@@ -0,0 +1,2 @@
+model,winning hyperparameters
+xg_boost,"max_depth:3, min_child_weight:3, gamma:0.2, colsample_bytree:0.6, objective:reg:squarederror, reg_alpha :0.9, "
diff --git a/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/output_vector/xg_boost_test.csv b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/output_vector/xg_boost_test.csv
new file mode 100644
index 0000000..9d35f1d
--- /dev/null
+++ b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/output_vector/xg_boost_test.csv
@@ -0,0 +1,162 @@
+,sectarian_language,quoted_sources,bias,factive_verbs,implicative_verbs,hedges,report_verbs,assertive_verbs,consistency_score,label,predicted
+0,0.0,1.0,0.209677419,0.0,0.0,0.0,0.024193548,0.016129031999999998,0.105813416,1,1
+1,0.0,0.5,0.280898876,0.0,0.0,0.005617978,0.028089888,0.011235955,0.146692266,1,1
+2,0.012987013,1.0,0.32034632,0.0,0.0,0.004329004,0.060606061,0.038961039,0.658274347,1,1
+3,0.042253521,0.5,0.323943662,0.0,0.0,0.007042254,0.042253521,0.035211268,0.057122168,0,0
+4,0.055555556,0.5,0.35714285700000004,0.0,0.0,0.0,0.055555556,0.03968254,0.019610841,0,0
+5,0.01,1.0,0.316666667,0.0,0.0,0.006666666999999999,0.056666667,0.033333333,0.445144912,1,1
+6,0.016129031999999998,1.0,0.333333333,0.005376344,0.005376344,0.005376344,0.059139785,0.059139785,0.006582929,1,1
+7,0.0,1.0,0.294871795,0.004273504,0.0,0.012820513,0.064102564,0.047008547000000005,0.151525599,1,1
+8,0.004854369,1.0,0.325242718,0.0,0.0,0.0,0.038834951,0.024271845,0.123849485,1,1
+9,0.0048154090000000005,1.0,0.242375602,0.0,0.006420546,0.008025682,0.033707865,0.016051364,0.064149177,1,1
+10,0.0,1.0,0.326530612,0.0,0.0,0.040816327,0.040816327,0.040816327,0.233795802,0,1
+11,0.07792207799999999,0.5,0.311688312,0.0,0.006493506,0.0,0.038961039,0.006493506,0.0044057440000000005,0,0
+12,0.0,1.0,0.355231144,0.00729927,0.00243309,0.02189781,0.051094891,0.024330900000000003,0.8157189229999999,1,1
+13,0.0,0.5,0.189873418,0.0,0.0,0.025316456,0.037974684,0.037974684,0.04070435,1,1
+14,0.0,0.0,0.233009709,0.0,0.0,0.0,0.019417476,0.0,0.107765553,0,0
+15,0.075757576,1.0,0.348484848,0.0,0.0,0.007575758,0.053030303,0.045454545,-1.0,0,0
+16,0.020408163,0.0,0.244897959,0.0,0.0,0.010204082,0.020408163,0.010204082,0.16871140699999998,0,1
+17,0.054347826,0.5,0.27173913,0.0,0.0,0.0,0.02173913,0.0,0.109375864,0,0
+18,0.008888889,1.0,0.297777778,0.0,0.0044444440000000005,0.008888889,0.035555556,0.031111111,0.11868222,1,1
+19,0.0,1.0,0.254098361,0.0,0.0,0.008196721,0.040983607000000005,0.016393443,0.055791191,0,1
+20,0.040322581,1.0,0.298387097,0.008064515999999999,0.0,0.016129031999999998,0.072580645,0.064516129,0.149293931,0,0
+21,0.0,0.5,0.267857143,0.0,0.0,0.0,0.071428571,0.017857143,0.208131154,1,1
+22,0.033557047,0.5,0.288590604,0.0,0.013422819,0.0,0.033557047,0.020134228,0.041087402,0,0
+23,0.0,1.0,0.329501916,0.003831418,0.0,0.007662835,0.034482759,0.026819923,0.632374195,0,1
+24,0.053435115,1.0,0.244274809,0.0,0.0,0.0,0.045801527,0.022900763,0.278960832,0,0
+25,0.059139785,1.0,0.333333333,0.0,0.001792115,0.001792115,0.08243727599999999,0.071684588,0.112401699,0,0
+26,0.010050251,1.0,0.266331658,0.0,0.0,0.0,0.035175879,0.025125628,0.616974535,1,1
+27,0.011363636000000002,1.0,0.284090909,0.0,0.0,0.0,0.045454545,0.056818182,0.7902525020000001,1,1
+28,0.04676259,1.0,0.255395683,0.0,0.0,0.003597122,0.050359712,0.035971223,0.099761731,0,0
+29,0.028169014,0.5,0.169014085,0.0,0.0,0.0,0.042253521,0.014084507,0.054309585,0,0
+30,0.135802469,0.5,0.308641975,0.012345678999999998,0.0,0.0,0.049382715999999986,0.024691358,0.100893354,0,0
+31,0.006666666999999999,0.5,0.3,0.0,0.0,0.0,0.026666667,0.013333333,0.001083333,1,1
+32,0.010067114,0.5,0.345637584,0.003355705,0.006711409000000001,0.006711409000000001,0.033557047,0.023489933,0.528006548,0,1
+33,0.047619048,0.5,0.257142857,0.0,0.019047619,0.0,0.028571429,0.028571429,0.151662367,0,0
+34,0.021621622000000004,1.0,0.32972973,0.0,0.005405405,0.021621622000000004,0.043243243,0.043243243,0.187961787,0,0
+35,0.0,0.5,0.354679803,0.004926108,0.0,0.0,0.019704433,0.009852217,0.427069717,1,1
+36,0.004140787,1.0,0.289855072,0.002070393,0.0,0.010351967,0.060041408,0.037267081,0.573589881,1,1
+37,0.023890785,1.0,0.26962457300000003,0.0,0.0,0.010238908,0.044368601,0.040955631,-1.0,0,0
+38,0.02027027,0.5,0.256756757,0.0,0.0,0.0,0.033783784,0.02027027,0.040670736,0,0
+39,0.0,1.0,0.273607748,0.0,0.004842615,0.007263923,0.021791768,0.014527845,0.234712468,1,1
+40,0.0,1.0,0.27014218,0.0,0.002369668,0.004739335999999999,0.026066351,0.016587678,0.314045802,1,1
+41,0.013513514,1.0,0.313513514,0.005405405,0.005405405,0.010810811000000002,0.045945946,0.032432432000000004,0.573589881,1,1
+42,0.004761905,1.0,0.319047619,0.0,0.0,0.004761905,0.05714285700000001,0.047619048,0.06462992599999999,1,1
+43,0.0,1.0,0.23890785,0.0068259390000000005,0.0,0.0068259390000000005,0.061433447,0.034129693,0.062274177,1,1
+44,0.043243243,0.5,0.291891892,0.0,0.0,0.010810811000000002,0.021621622000000004,0.021621622000000004,0.008819984,0,0
+45,0.02919708,1.0,0.328467153,0.003649635,0.0,0.01459854,0.058394160999999986,0.03649635,0.168369983,0,0
+46,0.053333333,0.5,0.32,0.0,0.0,0.0,0.053333333,0.026666667,0.038912684,0,0
+47,0.0,1.0,0.29054054100000004,0.006756757,0.0,0.006756757,0.027027027,0.02027027,0.00392402,1,1
+48,0.010245902,1.0,0.290983607,0.00204918,0.004098361,0.010245902,0.055327869,0.049180328,5.043260318,1,1
+49,0.029411765,0.5,0.343137255,0.0,0.0,0.019607843,0.06862745099999999,0.039215686,0.018852346,0,0
+50,0.0,1.0,0.359375,0.0,0.0,0.015625,0.046875,0.046875,0.110848887,0,0
+51,0.006472492,1.0,0.336569579,0.003236246,0.003236246,0.006472492,0.071197411,0.042071197000000005,0.187130905,1,1
+52,0.008064515999999999,1.0,0.282258065,0.0,0.0,0.02016129,0.044354839000000014,0.028225806000000006,0.534184541,1,1
+53,0.0,1.0,0.394904459,0.0,0.006369427,0.0,0.038216561,0.01910828,0.421900513,0,0
+54,0.009727626,1.0,0.276264591,0.003891051,0.0,0.005836576,0.054474708,0.036964981,0.180038948,1,1
+55,0.078431373,0.5,0.254901961,0.0,0.006535948000000001,0.0,0.045751634000000006,0.013071895,0.179888778,0,0
+56,0.0,0.5,0.35593220299999995,0.0,0.0,0.0,0.016949153,0.016949153,0.213953316,1,0
+57,0.039215686,0.0,0.333333333,0.0,0.0,0.0,0.078431373,0.05882352900000001,0.16871140699999998,0,0
+58,0.009389671,1.0,0.309859155,0.0,0.009389671,0.004694836,0.028169014,0.028169014,0.092375864,0,1
+59,0.0,0.5,0.28571428600000004,0.003246753,0.0,0.0,0.042207792,0.022727273,0.362149177,1,1
+60,0.009584665,1.0,0.290734824,0.0,0.0,0.006389776,0.038338658,0.028753994,0.436918351,1,1
+61,0.012931034,1.0,0.297413793,0.004310345,0.0,0.010775862,0.049568966,0.045258621,0.242379135,1,1
+62,0.016393443,0.5,0.37704918,0.0,0.0,0.016393443,0.032786885,0.032786885,0.10893222,0,1
+63,0.031007752000000006,0.0,0.17054263600000005,0.0,0.007751938000000002,0.0,0.023255814,0.023255814,0.283339464,0,0
+64,0.01754386,1.0,0.289473684,0.0,0.00877193,0.01754386,0.057017544,0.030701754,0.030423139,1,1
+65,0.037735849,0.5,0.301886792,0.0,0.009433962,0.0,0.047169811,0.028301887,0.207543052,0,0
+66,0.015873016,0.5,0.301587302,0.0,0.0,0.0,0.079365079,0.079365079,0.095697524,0,1
+67,0.0,1.0,0.331325301,0.006024096,0.0,0.0,0.054216867,0.036144578,0.278208357,0,0
+68,0.0,1.0,0.265822785,0.004219409,0.0,0.012658228,0.046413502,0.033755274,0.061065843,1,1
+69,0.070588235,0.5,0.317647059,0.0,0.0,0.0,0.082352941,0.035294118,0.191104114,0,0
+70,0.0072072069999999985,1.0,0.30630630600000003,0.003603604,0.001801802,0.0072072069999999985,0.068468468,0.055855856,0.976177723,1,1
+71,0.042372881,1.0,0.254237288,0.0,0.0,0.0,0.059322034,0.059322034,0.067871017,0,0
+72,0.021126761,1.0,0.299295775,0.0,0.003521127,0.007042254,0.056338028,0.038732394,0.307287854,0,0
+73,0.0,0.5,0.352422907,0.004405286,0.004405286,0.008810573,0.052863435999999986,0.026431718,0.35184888700000005,1,1
+74,0.015873016,0.5,0.333333333,0.0,0.0,0.007936508,0.047619048,0.047619048,0.006059466,0,1
+75,0.0,1.0,0.233576642,0.0,0.0,0.00729927,0.094890511,0.065693431,0.674052256,1,1
+76,0.002531646,1.0,0.248101266,0.002531646,0.007594936999999999,0.0,0.043037975,0.025316456,0.145692266,1,1
+77,0.050724638,0.5,0.326086957,0.0,0.0,0.007246376999999998,0.043478261,0.028985507,0.102268354,0,0
+78,0.044585987,0.5,0.299363057,0.006369427,0.012738854,0.0,0.031847134,0.012738854,0.246540524,0,0
+79,0.0,0.5,0.347826087,0.0,0.0,0.0,0.086956522,0.065217391,0.022943152,1,0
+80,0.0,0.5,0.269230769,0.0,0.004273504,0.004273504,0.025641026,0.017094017,2.539230533,1,1
+81,0.06122449,0.5,0.306122449,0.0,0.010204082,0.0,0.06122449,0.020408163,0.087440155,0,0
+82,0.0,1.0,0.233201581,0.0,0.0,0.007905138,0.079051383,0.067193676,0.49746245,1,1
+83,0.0,1.0,0.320512821,0.0,0.0,0.0,0.02991453,0.017094017,0.24106541,1,1
+84,0.010309278,1.0,0.371134021,0.0,0.0,0.0,0.082474227,0.06185567,0.223428986,1,1
+85,0.0,0.5,0.320512821,0.0,0.0,0.0,0.012820513,0.012820513,0.234712468,1,1
+86,0.002785515,1.0,0.278551532,0.005571031,0.002785515,0.005571031,0.050139276,0.033426184,0.503089881,1,1
+87,0.0,0.5,0.25698324,0.005586592,0.005586592,0.016759777,0.022346369,0.011173184,0.101538462,0,1
+88,0.032485876000000004,1.0,0.244350282,0.0,0.001412429,0.009887006,0.031073446,0.02259887,0.227525976,0,0
+89,0.009469697,1.0,0.306818182,0.001893939,0.0,0.015151515,0.0625,0.043560606,0.8348594890000001,1,1
+90,0.010869565,1.0,0.22826087,0.0,0.005434783,0.016304348,0.048913043,0.038043478,0.041019941,1,1
+91,0.020779221,1.0,0.29610389600000003,0.0,0.0,0.007792208,0.031168831,0.025974026,0.023177994,0,0
+92,0.06779661,0.0,0.313559322,0.0,0.0,0.008474576,0.042372881,0.016949153,0.174801375,0,0
+93,0.067567568,1.0,0.277027027,0.0,0.0,0.0,0.033783784,0.02027027,0.308534385,0,0
+94,0.037313433,0.0,0.305970149,0.0,0.007462687,0.0,0.0,0.0,0.13662375,0,0
+95,0.00625,1.0,0.35,0.0,0.003125,0.0,0.04375,0.03125,0.22506951,1,1
+96,0.008237231999999999,1.0,0.301482702,0.0,0.008237231999999999,0.021416804,0.074135091,0.05601318,0.097322006,1,1
+97,0.00483871,1.0,0.30322580600000004,0.0,0.008064515999999999,0.003225806,0.051612903,0.037096774,0.235545802,1,1
+98,0.0,1.0,0.308333333,0.0,0.0,0.0,0.058333333,0.033333333,0.601374195,0,1
+99,0.028818444,1.0,0.293948127,0.005763689000000001,0.002881844,0.005763689000000001,0.066282421,0.037463977,0.258965853,1,0
+100,0.006802720999999999,1.0,0.346938776,0.0,0.003401361,0.003401361,0.06802721099999999,0.040816327,0.085412394,1,1
+101,0.013605442,0.5,0.292517007,0.0,0.0,0.0,0.06122449,0.034013605,0.231968284,1,1
+102,0.020527859,1.0,0.302052786,0.0,0.002932551,0.014662757,0.041055718,0.035190616,0.208922821,0,0
+103,0.048076923,0.5,0.224358974,0.0,0.0,0.0,0.038461538,0.016025641,0.048018075999999986,0,0
+104,0.043373494000000005,1.0,0.402409639,0.0,0.002409639,0.004819277,0.091566265,0.069879518,0.24615979,0,0
+105,0.011958146,1.0,0.272047833,0.0014947679999999998,0.0014947679999999998,0.00896861,0.035874439,0.025411061,0.8035409,1,1
+106,0.0,0.5,0.227692308,0.0,0.0,0.003076923,0.015384615,0.009230769,0.150567266,1,1
+107,0.028301887,1.0,0.251572327,0.003144654,0.0,0.006289308,0.059748428,0.050314465,0.030080763,0,0
+108,0.050458716,0.5,0.298165138,0.0,0.002293578,0.002293578,0.043577982,0.027522936,0.156848958,0,0
+109,0.043165468,1.0,0.287769784,0.0,0.0,0.0,0.043165468,0.035971223,-1.0,0,0
+110,0.010928962,0.5,0.25136612,0.0,0.0,0.010928962,0.043715847,0.038251366,0.107765553,1,1
+111,0.0,1.0,0.287593985,0.001879699,0.007518797,0.001879699,0.041353383,0.037593985,0.108598887,1,1
+112,0.0456621,0.5,0.283105023,0.0,0.0,0.0,0.03652968,0.01369863,0.16986078100000002,0,0
+113,0.011560694,1.0,0.375722543,0.0,0.005780347,0.011560694,0.052023121,0.040462428,0.319335446,1,1
+114,0.0,1.0,0.316546763,0.0,0.010791367,0.035971223,0.032374101,0.021582734,0.066125,1,1
+115,0.090909091,1.0,0.257575758,0.0,0.015151515,0.045454545,0.060606061,0.060606061,0.08350249900000001,0,0
+116,0.041958042,1.0,0.248251748,0.0,0.0,0.0,0.031468531,0.01048951,0.515906553,0,0
+117,0.038888889,0.5,0.238888889,0.0,0.0,0.0,0.033333333,0.011111111000000002,0.21992693,0,0
+118,0.070175439,1.0,0.245614035,0.0,0.0,0.01754386,0.052631579000000005,0.052631579000000005,0.16871140699999998,0,0
+119,0.0,0.5,0.306451613,0.0,0.0,0.008064515999999999,0.040322581,0.016129031999999998,0.503089881,1,1
+120,0.0078125,1.0,0.2265625,0.0,0.0,0.0,0.0625,0.0546875,0.01972135,1,1
+121,0.010752688,0.5,0.268817204,0.0,0.0,0.0,0.043010753,0.021505376,0.106652686,1,1
+122,0.076923077,1.0,0.355769231,0.0,0.0,0.009615385,0.057692308,0.057692308,0.043690653,0,0
+123,0.0,1.0,0.266375546,0.0,0.0,0.021834061,0.043668122,0.03930131,0.110981022,1,1
+124,0.009049774,0.5,0.21719457,0.004524887,0.009049774,0.0,0.040723982,0.013574661000000002,0.039186608,0,1
+125,0.019230769,1.0,0.352564103,0.0,0.012820513,0.012820513,0.064102564,0.051282051,1.102239616,1,1
+126,0.0,1.0,0.279329609,0.0,0.0,0.005586592,0.06424581,0.055865922,0.147942266,1,1
+127,0.0,1.0,0.341207349,0.005249344,0.0,0.023622047,0.091863517,0.060367454,0.514052256,0,0
+128,0.025974026,0.5,0.37012987,0.0,0.0,0.012987013,0.038961039,0.019480519,0.10893222,0,0
+129,0.030567686,1.0,0.292576419,0.0,0.004366812,0.004366812,0.043668122,0.026200873,0.505839881,0,0
+130,0.0,0.5,0.31972789100000004,0.0,0.0,0.006802720999999999,0.06122449,0.06122449,0.466968923,1,0
+131,0.051546392,0.5,0.262886598,0.005154639,0.0,0.0,0.041237113,0.025773196,0.06005238900000001,0,0
+132,0.0,0.5,0.28571428600000004,0.0,0.0,0.0,0.026455026,0.015873016,0.145317266,1,1
+133,0.025974026,1.0,0.324675325,0.0,0.006493506,0.006493506,0.045454545,0.032467532,0.236129135,0,0
+134,0.02359882,1.0,0.324483776,0.0,0.002949853,0.01179941,0.03539823,0.026548673,0.058,1,0
+135,0.005586592,1.0,0.28491620100000004,0.005586592,0.003724395,0.009310987,0.040968343,0.026070764,0.617589881,1,1
+136,0.003759398,1.0,0.265037594,0.0,0.0,0.009398496,0.05075188,0.039473684,0.073774177,1,1
+137,0.0,1.0,0.329113924,0.0,0.0,0.0,0.037974684,0.037974684,0.354527689,0,0
+138,0.04519774,1.0,0.322033898,0.0,0.0,0.005649718000000001,0.04519774,0.028248588,0.037443389,0,0
+139,0.013422819,1.0,0.285234899,0.0,0.003355705,0.0,0.036912752,0.036912752,0.243096209,1,1
+140,0.0,0.5,0.236111111,0.0,0.0,0.0,0.055555556,0.041666667,0.107765553,1,1
+141,0.05882352900000001,0.0,0.235294118,0.0,0.0,0.0,0.0,0.0,0.033263754,0,0
+142,0.0,1.0,0.313043478,0.0,0.0,0.0,0.060869565,0.034782609,-1.0,0,1
+143,0.018348624,1.0,0.316513761,0.0,0.0,0.0,0.036697248,0.02293578,0.16878664899999998,1,1
+144,0.057894737,0.5,0.3,0.0,0.005263158,0.010526316,0.036842105,0.021052632,0.090299571,0,0
+145,0.0,1.0,0.268907563,0.0,0.004201681,0.008403361,0.06302521,0.037815126,0.17805451600000002,1,1
+146,0.012618297,1.0,0.277602524,0.0,0.0,0.0063091480000000005,0.03785489,0.028391167,0.247796453,1,1
+147,0.025380711,0.5,0.289340102,0.0,0.0,0.0050761420000000005,0.035532995,0.020304569,0.063296592,0,0
+148,0.027027027,1.0,0.34054054100000003,0.0,0.0,0.016216216000000002,0.054054054,0.048648649,0.134975474,0,0
+149,0.0,1.0,0.28571428600000004,0.0,0.002232143,0.006696429,0.024553571,0.017857143,0.354408115,1,1
+150,0.0,0.0,0.214285714,0.0,0.0,0.0,0.0,0.0,0.097697524,0,0
+151,0.014492753999999997,0.5,0.198067633,0.0,0.0,0.004830918,0.033816425,0.024154589,0.281422821,1,1
+152,0.0,1.0,0.367346939,0.0,0.0,0.0,0.040816327,0.040816327,0.061690843,0,0
+153,0.0,1.0,0.317391304,0.0,0.0,0.02173913,0.034782609,0.026086957,0.209714487,0,1
+154,0.082474227,0.5,0.298969072,0.0,0.0,0.0,0.030927835,0.030927835,0.116506123,0,0
+155,0.02247191,1.0,0.25842696600000004,0.0,0.0,0.0,0.02247191,0.011235955,0.02409635,1,1
+156,0.038910506,0.5,0.284046693,0.007782101,0.007782101,0.0,0.050583658,0.031128405,0.039363232000000005,0,0
+157,0.0,0.5,0.248407643,0.0,0.0,0.0,0.01910828,0.006369427,0.30749301100000004,1,1
+158,0.0,1.0,0.274509804,0.0,0.0,0.019607843,0.039215686,0.039215686,0.07561798,1,1
+159,0.009756098,1.0,0.331707317,0.004878049000000001,0.0,0.009756098,0.053658537,0.034146341000000004,0.243971183,1,1
+160,0.0,0.5,0.25,0.0,0.0,0.0,0.045454545,0.045454545,0.225152843,1,1
diff --git a/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/risk_df_xg_boost.csv b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/risk_df_xg_boost.csv
new file mode 100644
index 0000000..76cc0c6
--- /dev/null
+++ b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/risk_df_xg_boost.csv
@@ -0,0 +1,162 @@
+test_indices,y_test,y_pred,risk_scores,quantiles
+29.0,0.0,0.0,1.188626766204834,9
+46.0,0.0,0.0,1.180782437324524,9
+138.0,0.0,0.0,1.1284294128417969,9
+4.0,0.0,0.0,1.1047955751419067,9
+122.0,0.0,0.0,1.0974632501602173,9
+3.0,0.0,0.0,1.064728021621704,9
+22.0,0.0,0.0,1.055997371673584,9
+38.0,0.0,0.0,1.054558515548706,9
+57.0,0.0,0.0,1.011232614517212,9
+91.0,0.0,0.0,1.0084741115570068,9
+24.0,0.0,0.0,1.005315899848938,9
+49.0,0.0,0.0,1.002187967300415,9
+148.0,0.0,0.0,0.9954482316970825,9
+131.0,0.0,0.0,0.9892945289611816,9
+103.0,0.0,0.0,0.9892224073410034,9
+55.0,0.0,0.0,0.9788601398468018,9
+77.0,0.0,0.0,0.9540582895278931,9
+69.0,0.0,0.0,0.952783465385437,8
+15.0,0.0,0.0,0.9523149728775024,8
+94.0,0.0,0.0,0.9496227502822876,8
+107.0,0.0,0.0,0.944963812828064,8
+30.0,0.0,0.0,0.939215898513794,8
+11.0,0.0,0.0,0.9348745346069336,8
+93.0,0.0,0.0,0.929614782333374,8
+134.0,1.0,0.0,0.9293075799942017,8
+20.0,0.0,0.0,0.9265545606613159,8
+147.0,0.0,0.0,0.9260814189910889,8
+109.0,0.0,0.0,0.9250591993331909,8
+128.0,0.0,0.0,0.9210649728775024,8
+92.0,0.0,0.0,0.9187052249908447,8
+71.0,0.0,0.0,0.9171491861343384,8
+28.0,0.0,0.0,0.903677225112915,8
+25.0,0.0,0.0,0.8983654975891113,8
+81.0,0.0,0.0,0.8950351476669312,7
+118.0,0.0,0.0,0.8942840695381165,7
+141.0,0.0,0.0,0.8903558254241943,7
+112.0,0.0,0.0,0.8874168395996094,7
+65.0,0.0,0.0,0.8873482942581177,7
+37.0,0.0,0.0,0.8847885131835938,7
+150.0,0.0,0.0,0.8834140300750732,7
+154.0,0.0,0.0,0.8706315755844116,7
+156.0,0.0,0.0,0.8614803552627563,7
+116.0,0.0,0.0,0.856704592704773,7
+117.0,0.0,0.0,0.8527312278747559,7
+104.0,0.0,0.0,0.8461925983428955,7
+108.0,0.0,0.0,0.8449972867965698,7
+88.0,0.0,0.0,0.837355375289917,7
+78.0,0.0,0.0,0.8272164463996887,7
+14.0,0.0,0.0,0.8125984072685242,7
+45.0,0.0,0.0,0.7949563264846802,6
+72.0,0.0,0.0,0.7836992740631104,6
+129.0,0.0,0.0,0.7707080841064453,6
+44.0,0.0,0.0,0.7706748843193054,6
+17.0,0.0,0.0,0.7468796372413635,6
+79.0,1.0,0.0,0.7445447444915771,6
+33.0,0.0,0.0,0.7369860410690308,6
+102.0,0.0,0.0,0.7016257047653198,6
+115.0,0.0,0.0,0.6873418092727661,6
+99.0,1.0,0.0,0.6870071887969971,6
+144.0,0.0,0.0,0.6832019686698914,6
+133.0,0.0,0.0,0.6820499897003174,6
+130.0,1.0,0.0,0.6378527879714966,6
+63.0,0.0,0.0,0.6244765520095825,6
+34.0,0.0,0.0,0.6080209016799927,6
+50.0,0.0,0.0,0.5949207544326782,6
+137.0,0.0,0.0,0.5676370859146118,5
+152.0,0.0,0.0,0.560978889465332,5
+56.0,1.0,0.0,0.5426477789878845,5
+53.0,0.0,0.0,0.520418643951416,5
+127.0,0.0,0.0,0.5197881460189819,5
+67.0,0.0,0.0,0.5117042064666748,5
+10.0,0.0,1.0,0.4980916380882263,5
+83.0,1.0,1.0,0.4887915849685669,5
+155.0,1.0,1.0,0.4806191921234131,5
+19.0,0.0,1.0,0.4717666506767273,5
+142.0,0.0,1.0,0.4717411994934082,5
+119.0,1.0,1.0,0.45121312141418457,5
+23.0,0.0,1.0,0.42213618755340576,5
+124.0,0.0,1.0,0.4013211727142334,5
+35.0,1.0,1.0,0.3977862596511841,5
+85.0,1.0,1.0,0.3869025707244873,5
+98.0,0.0,1.0,0.36841511726379395,4
+74.0,0.0,1.0,0.35037291049957275,4
+9.0,1.0,1.0,0.3397291898727417,4
+153.0,0.0,1.0,0.3318742513656616,4
+21.0,1.0,1.0,0.3114848732948303,4
+16.0,0.0,1.0,0.2737446427345276,4
+2.0,1.0,1.0,0.2701190710067749,4
+13.0,1.0,1.0,0.26431095600128174,4
+42.0,1.0,1.0,0.2573915719985962,4
+12.0,1.0,1.0,0.23527991771697998,4
+140.0,1.0,1.0,0.22368919849395752,4
+66.0,0.0,1.0,0.21455353498458862,4
+159.0,1.0,1.0,0.20377129316329956,4
+75.0,1.0,1.0,0.20316541194915771,4
+8.0,1.0,1.0,0.1904279589653015,4
+68.0,1.0,1.0,0.19015789031982422,4
+6.0,1.0,1.0,0.18693745136260986,3
+158.0,1.0,1.0,0.1731356978416443,3
+62.0,0.0,1.0,0.17068636417388916,3
+84.0,1.0,1.0,0.16990172863006592,3
+90.0,1.0,1.0,0.16143429279327393,3
+160.0,1.0,1.0,0.1583641767501831,3
+5.0,1.0,1.0,0.15796923637390137,3
+59.0,1.0,1.0,0.15669608116149902,3
+73.0,1.0,1.0,0.15577858686447144,3
+114.0,1.0,1.0,0.15567141771316528,3
+82.0,1.0,1.0,0.15174615383148193,3
+123.0,1.0,1.0,0.1474427580833435,3
+126.0,1.0,1.0,0.12486863136291504,3
+121.0,1.0,1.0,0.12161839008331299,3
+31.0,1.0,1.0,0.12139970064163208,3
+120.0,1.0,1.0,0.11404061317443848,3
+125.0,1.0,1.0,0.09862512350082397,2
+143.0,1.0,1.0,0.078188955783844,2
+7.0,1.0,1.0,0.07423287630081177,2
+132.0,1.0,1.0,0.07396769523620605,2
+27.0,1.0,1.0,0.07099521160125732,2
+113.0,1.0,1.0,0.07016384601593018,2
+95.0,1.0,1.0,0.06893110275268555,2
+111.0,1.0,1.0,0.0684976577758789,2
+64.0,1.0,1.0,0.06641650199890137,2
+89.0,1.0,1.0,0.06625425815582275,2
+0.0,1.0,1.0,0.0585629940032959,2
+101.0,1.0,1.0,0.05591261386871338,2
+151.0,1.0,1.0,0.04563486576080322,2
+146.0,1.0,1.0,0.04563486576080322,2
+145.0,1.0,1.0,0.04223942756652832,2
+157.0,1.0,1.0,0.04133641719818115,2
+32.0,0.0,1.0,0.037929654121398926,1
+40.0,1.0,1.0,0.037558913230895996,1
+149.0,1.0,1.0,0.037558913230895996,1
+106.0,1.0,1.0,0.03670567274093628,1
+97.0,1.0,1.0,0.03347146511077881,1
+136.0,1.0,1.0,0.032715797424316406,1
+26.0,1.0,1.0,0.030872702598571777,1
+1.0,1.0,1.0,0.02797842025756836,1
+60.0,1.0,1.0,0.022069454193115234,1
+110.0,1.0,1.0,0.020595788955688477,1
+80.0,1.0,1.0,0.0190732479095459,1
+100.0,1.0,1.0,0.015226960182189941,1
+105.0,1.0,1.0,0.008894383907318115,1
+61.0,1.0,1.0,0.005540430545806885,1
+43.0,1.0,1.0,-0.00035250186920166016,1
+139.0,1.0,1.0,-0.0037429332733154297,1
+39.0,1.0,1.0,-0.004706621170043945,0
+54.0,1.0,1.0,-0.008504390716552734,0
+76.0,1.0,1.0,-0.012294769287109375,0
+41.0,1.0,1.0,-0.021587491035461426,0
+52.0,1.0,1.0,-0.02192842960357666,0
+47.0,1.0,1.0,-0.04618263244628906,0
+70.0,1.0,1.0,-0.0497894287109375,0
+36.0,1.0,1.0,-0.05404174327850342,0
+51.0,1.0,1.0,-0.055544137954711914,0
+86.0,1.0,1.0,-0.06344783306121826,0
+48.0,1.0,1.0,-0.06489968299865723,0
+135.0,1.0,1.0,-0.07162928581237793,0
+87.0,0.0,1.0,-0.07438910007476807,0
+58.0,0.0,1.0,-0.07677698135375977,0
+96.0,1.0,1.0,-0.09078371524810791,0
+18.0,1.0,1.0,-0.09917163848876953,0
diff --git a/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/xg_boost.pickle b/Experiments/Shallow/Experiment1/output_xgboost_poslabel0/trained_models/xg_boost.pickle
new file mode 100644
index 0000000000000000000000000000000000000000..b4ec570c0ea178bb457168d8db33fc909e772b54
GIT binary patch
literal 63161
zcmeI52UHYE*Y`&O6+}f>F)S)7<^)DEJ>3{q5c7%=2N+<KG|Y$*9gL`$vui+17}lI6
zi8<%&u9$ONbzRr+)vfLxx~5v0=h;2)2k&|NoW<$t>gwvQU)}oOTh+Y=i;$t=!7(v9
zeG}cFNVO_1+9t3a%SEbmI!%~H9cQCe)KAnFNzfLp7ig<cD58VZI=v=JrH_fzX)XLh
z1FcbFOz=Q;h+Y$~)>;PIq5U{@xVug}SQV!ZRma7}#A&T?wkXxmpip(JK0;f}&myoC
z%7`zhi4G5nQ|Z;(;sH2YygDv8MyJsa)0PMbERJ&F>Z#+j)&YSf(XKvDtqzJ(>my=9
zwKf5PRwyZ46&0n@mTc#9Y$0rma4n)V(Lo^*n#j<gA!<!{gkEclu38%9=IaruR|V<x
z>R4?l{<6Bk!8%n`Y@}LSIsl&^5);WM1O*R+Yii51^SRp`Z-He|G1B9a>Uede){Z_g
zIwn-DEz4g4J(eI<WNd^=TP`5b29*E_k*cWRP?h!v{#0FvDpDO38>18JT%OMvtkS82
zbRjWuYHbDnp+sp=3q^-(?c0t1fQmvJu2l5ksGwL?oGLO>9T|jcT`?fA7&<y=h$=2z
zr>&Hrt!%tDu8gC$N;{utCt*9K3oL=M2C={cdf-1A*?=qC2+1~D2ZTh`1Z}l?xDmtD
zD*fO%bx^b_O0CmY@27RF7g!V(6XvX~!T)g4*5rRQ)7IjDG}k)uKU!#O^FLZ@>+nBX
zY3uSoT5E-JT($Mp#Fg~JV$qcv@HZBriVj7M)-WV^uqINkiPqVm=0YIHsfO8T8?j4X
zD->L(fVMxiYaA06rc>+P`#wUI<2N6m7q%k&KgNHB-T#q)pvS;w+H0WIU<(h1b__+o
z#9HFy0`>>$Rz^}M@ySY({>OiQMH|!$XhdKe1}4qUL_ZA{=#M4(5B+P{z3Pe&`l$dj
z0#6*J8`d1N$VBHE!1zFifHYOt+ul$X+!yp+IM@G5B?gsk0ILMX5z=zP?)kv=z`TL6
zL1h>MxvVTW2K9jrB`balpPzx!6nqMwwqf16bhwr@?exi$UQkz)v~*NoBA;VunkU?Y
zG~c_QmSv!OBJ!aunQ))dd}F&_@EZL?U!@}3(KpDqr58G^cvj&9dM+MZt0x}t%oJsu
ziYgU~dz?jsQr@ut!KXJm-h|s{2+V~0ouI0O_B$)1Z?y7;{Xc%K$0!W5xdk<=d%=F^
zsht>wq6YWJfmD1PC84b(cc|w`Tt2^V%ieRHmcjqVf0gUkt;5&j(^43;pLg6afs5^y
zjO)uEKdW4xF-}rm3e%&<CCR=6SFy@wTpqL~w2`<KG+t4?45hU#;a-ir0+S_1p3Q<f
zi@ZYnwhi>nf@9J)wQgVy3<H0dVf2q-wL+bR+QJ|*3~667>R?_)hJn8q&0ct$a(H!X
zGR0wHx%*zG9H!dOgEWFK?-T1O4#)pkmf~=jPfkY6jszAsRFC`QiHcDy=xeD|81{3Y
zqGsX#S5JAEK~?1XjNc(?*8$4VU+&@k>>YP~6o$QASo!6cv(BYvp#0O=qNUDe0Edcg
z$5H#cas7XNfVqVvg`zSSF?t~8g5U4UW#7w`>}M-?*B&m}_hkFmpPtF*g}+s~iC14s
z_H&ifZ!O3BB4_y8DChq+&RUH-lp*B|_?mnx8lFAD+5F5D%$dk2aQl05PKGIGQ4@Dl
zoIOe_LvdE}f;GiiSgCCUXK<}`GY>+Vkw-|Y>v}o;^QFJAz5Cj7Bj)UdY61hC{Z_pr
z=4`ROFN3PcHLE%r_ajsU+6E}EELe%#)ovk&^6%xw6bZ(hB{%kDfV0~#XY!m?eSqwe
z8&}#fRl-?U&iU{{Z(J1qQ;WM2{ZeAT9N4lu?o0L+?4_1-@%8v~T5-EiuaN9BjN`bi
zU?Z?LDCpyFsU!2D?nZkCWAcQdxA6Ul_6+Pvh26H;o{6>#SSk9<*#|fiZ5O1miuKr@
ziM9*Uy2css^Olakk28)^<8Q__M=#UycR&tD@z}m@0LA0&0}V1v?cT=ngQ@X%qtoeh
zs1q;;8?@7$Woro@A??7_SDsfZzV`vU*Xv3w=5Y}hfX350T>0wDaQj+5U54!13$AGZ
zgZU_`YlV(Gu%q5Hczk_x5XR##tlj?Sn7?}M1JS+**So=_bg(^6ev{GuOfIU@cAOus
zt5D=BkJ=RT=6}OqXXVElwIqDmDZ@@QlpKG?KIm9lay*@V;NdUfbua62Y(1_oUuG`T
zx%bq({D!Gq&G@4@KeS~*<`wK$_QVS4nUTCUana!W5qSmsHFU!+un|VR2yOoP-A95~
z;KgFtP+-%j7vZ<#*Q3}jio8O;a%#1=sa_1&>zZ!L>kzM1z$U?0aC`?(lxDPd&<;BW
zSD@@?ivR`~Ch|E?kKJd=>&BO5_M$W*pRHT6SEsBT%<Ih$buh0B)q4@2Pr0MjYU1{7
zwP`zgc8$2{@zXI6*LUng9JS#5?7v_h&z^YUtuV~wI)tyoJVu@>jq(@g+&aI){N6tF
z1?4Z#I=wtC;njtk_o}jlFNSg5HVNeuH(T!0u6p?Td`d-bY~{Zs`v=*EN=Mv&{PFT^
z*CFlG#j_QPH08;AFZbr{8<d*u8eD!s=M~kN(u?4GI40E1g8LD9h4vNoqSU?~DdP?{
z*JxjXP5b`IFt!oAu6AI+<{JGQ;MApV_e@h>RW3~_`}(?BG-Y4kR+&uM*UP<r0b5FN
zo!;Ar8t+>q1rXys+~=XtWXir??ENgg+>N$)ydRSG$^-Ik@4X7~x}Q54@*eZi{^T6Q
zpMmqLT^I9_WM$7N6zf>^o7SFizuEe~(DC`)*@P<aOcb9x<f8p)>~On2nAhwbj}a$s
z+_J1Lc>F<G(AJq9@ue*0hu^nkkB)AO%jfrNaZekCNsgD~CJs)N@Oo6)F21_txGUSx
zp^@bLid?(TyglN}E5Y`8e=q}ni@ZWzVJnEbGj+sasH;&AfDJXrzd`q8@D5vsb*HEY
zpd8V^5%qvr9y|llzQVc5{^<m-FgE+X-c0!8kaqhwSBlrMhUS!g9lN9jWnV`w+(X${
zLqls%Q~Ub!mQae<vvaL8S`R+LfF8L2d^P4Z>Fw``*L2Qm*)}g|Tj%{n5P##j_!{?d
zdn-~#xq<)P{L(ng--qHb-tXj!hVk|@e)MXzKZC7$vj*l>F%-CCxzoE!NqDtW?$+TL
z3AzGo2F9aw6$x*ZxtzHbBz$(`*s=B!J_jggty?6?AHiN)au1IWe0dYtBeT6F$G@;v
zo%s3}242ne#{;aFV*LsX!3NCjkLpkG3TYWHD!|xpw6E~MOZ+mD&;!8ByLSnMeuXl*
zGNUM75AL{1#g8igagX9vTmPE7seQH2N~7%Sv-QO&`&zT^Sc=z})YIu_?b=~pS3K^4
zdCln?hVAQtD|*c9)#A4iCk9SiE)DaV{nHG@#Q<e|A2-Zj`E_Mc{=J<4t*Lmtcf4sp
zyk1o%1XafSogXbl=c~DHwGQ$8VxSzA!MnOicrq|U=Wplx0~|L@<mMdDl<<0z{r%7F
zxPJI_g`?7ISu!eD+>(^P>vHqXSEMMX&g(5HzYABq*#>+ZcrEDhqk8cZ;ogk)6~^cp
zxp(pXqV~t}PB@-=aRvCiM*RwD=W7QOdH{50=pP)8cLIN~p?nI@XS;BFh&C5^PHd7)
z@Cx}to$M(6`f5vOV3Qc<Z)>e6J@EJDbrgqIO+CPt61ue2rz7d>*B-~Z)Uin!+|CY<
zULu|O8`ph!S<J!6z*Kbq?YY37vv7Z$dHW<fzK-kbHUp3IX<2rNyOZp+OZzc*P<MqQ
zg}Ldw5OWZ@U@JPG<0b}-m2misUG4cwq9cR2C660RxI4@aiTGWz&oFhor{VJW@^h8r
zKK&>;UY8rQW_1P}6YV0OuW*dxsIGV{hB}L!eM@)7|L#g~2AXw1T0_v7gk2nRY=SpR
zGmhim(w&1#mZWs&z8+DOT@2Z717kbEPn{!gDBW4PRUBm(ds;eEe*KMxhart9@9aYt
zkLI3Hn8${Sb?)e};^Rf&F`fHztT=A(-XFn#8PEAgHOK9J;ZA47Uo9@9^7DOgzg@?#
zNBci>Z`O~&JdRmW746Sp2UWGkygu_zK<BeuOJ$;jM<+HX<DrD7x2*O^8(cor0nJvh
zD;qtO>^J9@bv`c1-&vV;<tJ3GxJ9z<H<pv+ci^Ttt&;3lVjC;V<8fZ(6`lob1x<H?
zof9;s(e6MTYFWuj_<lrQfj{v7AwO^J_`mgB($e7`rD^lDjp5lFc?FvmRy7H1rIA-S
zZn?98kJL|sG7|bZc%U?*yzz`Bp*tbp%tQSNULnnL>Ya2{Ut|4HF^X3+t*JPaOF2Ad
z6Zt|GGSoQ!tcu0HyEmF)Ui;M>?GE>u(gfo0PVBab&zP?X)%PNP?S0F8R>SS>xW*oF
z<E(sNFBu<qtO@f+uasRU+2L`$qZ68MF<j^F?m3QmZI$*3aaEi9nD}QpJRg2DFpoMG
z#pUt)xy-~tHzj<<Dp#y@%M^1f6tT*y$I~UpuX5Ad-<O=9!mQCr$L*ua^P{DHzb)5%
z%=LXx9^50up$ZePU`wl8UrC4hi@ZWwV2F~?oxn)vw@vXl2fxK_VGIY)-pDKb_N~;P
z(w)JP-i#@)7KesWy0cxj1;y*f>rDyW3D@rKJ%!?R#n7EJufAT?ct7iYbBIkD`w85;
zdv>;0+`BE_;3ri-|Jn`OazL?bh(9ORx7jw#qwRrXnAbyBu3$az>hu!C$qeQ5lyaEQ
z<il1d|8C{in>BI%Ctv<Re12d%WQThJpRKoEK>IJbbyY56dkohFJ<!;xvxLXa$`f;M
zNO&|bXQz}y<%-(^WpcR)$?*qlvoZ@L$L*9Cc2~_S&+wf4>v09#zI+J`<D8O$>XFB*
zSaLzLufWUwTQP7iM%@Ya)%#sVTz`>Q$hY&;6l`C`I23TWF|m9$w4><PLt2h?7s5}1
zH2u$x1g}uuw6${y`wGt}wR9}OE2P<Mt?yx~I~Tt^x6f1$bokf~e0aic)~Uu)yoQ7f
z^n(5;_Aj``k?}Vv`#SV?mPhB|zhGWlpFNKJb%kR3k%NfO*IdILZE<_gPSc?0<j4j6
z%Im?~t!JU*Te+!E7I*-UT@HLk$3L;_n(HvH<+`jw`wQ5%{g+~1hg>R&^g$Zi$?J<d
z<mb0+#>KXMrnsjtY~r?QN}+xrZhP6DZ#GJJvt%Ews*{&r5y2imP(#A&4CVQ*9J;Q!
zG0fS6yCnHj*=Y}!;qpcM3hO9fD`>nzyRnH%^vp<J#d#^QO(9>hotr1RA7eWM8w<l;
zLYk3R$XBjxWz4I1F8rJ5v=fhi(lm$H!(i+;mIufF@C)`tX$on+8ymWKney8IV_k~Z
z2QAAGyh0hLuDvFBg|sd%9($y`LRy*8Q3S7$R_x(@k3{Qe%<GdUZCv3#+r^>rpHcYE
zWgM^$iZAg7aZ!}hyH>&c>8-Ay{YT0Mh9h|Ym!0W|lQ-PLdgJhTf3@Zzbi6Zbe{4QJ
zzF~ALbbK-UtbJ$ve9$G(Hbc2=j;Dk-XXVblP4aj%+~xxQE=llOf76Q${#^L$z+Res
zOmaS2m-6LDNnD>{Za;1#;dLH+eQp-PE7$_q3L3BAA7!<?PVfqCc`qKtThJ!jSID;@
z#Fmlr3U>3!h@*R@yh2*H3@ggMKDxCOw-;~#8(gE<y!{lfZTd8GH|6zem$8(;6*crJ
z*jyvmP}jIb7JMrs|ByCdu`j_Zq@^@95PAUWv)!r%*j!_IkoI|xW%}BV(=o4GzEpLE
zbGwhchj^{%o2K6A0ry=@xdL%iiQQN+4eO#=3MJaN^nG4-4IbZHTC7F;i&!VaFPP6)
zj{VVonsQ)5ZLAjtgx*11B`JG%U7p9Q;XW6-yu2i?G?`8Rt+#|nhTZIT5c36fg8nhd
zz9uSH+ziaBE43uNCMmbC?2#!RMURNdwv@(MJ1al7{0;LD_XPS?wDkpzS5!5FX`CO@
z=IAQp`xAKu4zv&E6Z5E$w&3;&y#4~(7dA+Hcr+B+#;9MxHa1zj+8dsM80QDOTI5*?
zLcgNJihe$03Hu6ZH}@9@TWaJGt}|rGeoDW_HJwTE>bb}w9qs|nfep&*wat;>71Fjv
z#8LWnMY}0pQ~K}5yiV9&8}oYUC#3UGe4v|R1s+%2e}ws?@m%Xq_i=mw<%i;+hF#p*
zUv-#2L%TYN8%O1!HQxCCi;tOr@|WXOO#2LY9{pH|Z@ywvG<7BV)slOe*;~TfAg(fZ
z2m3=%SM(^Dse#KS$FrHtzqF_vaeKsu{(J-1hfjH>JpRNgQ#^|JW}g)4AUSSe%G8X&
z=Zm(dpz;bFgd{Fw(7hP-E7;N^8(=*o+0F~cP6Qib<OY71b2^UwW>M3^xgQ5w5F7$0
z^NY+S;-Qdc)4&I8q_I4>-lpXX3BMoGO2@C+SNl|Z%uPv61MK%)uLa|yqwm{O$ME$b
zpF+Vf-EXLHyXZ!Eq5PG6Lv?9bN4i#=gYrL89tfL_IpOm=uz&X)n!*2uzh!*4b*%20
zx1Y_V7c=1U__W>1l2fPPb}kHdsM+6>pzcJw#y2^d1@{7d7{(K{8C)|uVLJqE0voiU
zM{YYjUWk4PjE6PvH_MXRA!vWa?NxiFb_mJ?`v>-jFOC1Z@DIg4({XdxWqLha)*^cT
zCNAPIHGgx_<p^j$!Vdkk*cM{s#_Ph(MZ{czG$P;Q$~pUH{n8Ed)brG%-H`8OJ2ZD-
zSi^PMF$LS9Ru$tAFN?U;GYfHh{}>ATKbLWtQ3sEUo~Mu>qgcrmudoT*rSrFIqyCbj
zoaOfc^R>nj)=$ph_RVrl7yCY{8q@9RWr^Kkm<9b(GvWID7R$ahNat@RaMnFnNyb@)
z^2V1{lKhPFOs^*rUN<WfCvKD2vGE+6y`11xX!8Q6^MEDOI3;=}hC2Ncas5SJfj_x8
zW$o=nskqPb*AXxV7{^U0uj~Dyz_4-LgfzR){fPM+Al5Op2H{6TT8CwI37rRNleUy3
zbRMK#czzwmNP@%YyPlNJ3x01!tv|ZGOGEf2sD297xi20ae*feJai0O+1NMOJNqDgb
zwX+lJ{Yy{GTa&$&5Wn`mzMWK<mq+mr5f@3yhnKJ6<C7CAq5Rp(&DB`U<H@nXDF1b?
zbH>k@-#N85Abx9e7r$(m@X9C;Z7C+<Erp5LR8nFuQ<T%rKa%iiV6MmRlpJR`mx!w9
zy5csN>)7U&gnv8s!2woMei5!tuZx&xxJS@7V&5rfIuBwzZ++T9-HrAYSX(r(TsBHG
z+E++}HE+N-umKw!&lx)z^D2&;kgv}Eu3%dXqRoZh?}n@gU&Uy@pd9PfcR;HV<=xlK
zB=j3x<LQ<edrUbDA2@ZNsok8TN+I+c)N%Z=(Oy!!32E*<Qay(DLH+^au;-{Dd*B-L
zhJ&4(#;sDU!FE$W8;!GuZCuy&6S2Pxd0<>#a3c)2^MX|)(eY&N<X<_MyZX~uG!LG}
z<vcoox%;)HA1ZINa_g;hFSu`hd%&I_6er=R4mYu$HqXB`q;fsB48nGT&(A1VuO5%D
zClsK3QMU&wSKJ0Dt=dg2G@J#O?u+_n9%sOwVWl0uAJHyCJ0Bih7W=;<Q;^T$?MW}_
zOVEC>!MJ?cClQ{t(Jn&1c5zb(&frNsz0sT)$02RJ%M>^1I1XvCZ;BJ~8o18wAJf5B
z8m|j!Js)LynDSU_yaV_c#(YrTz>zK<li#B_3F2&JvkjOtMaW{rjh(OW?VNpZKkMoy
zp!*-guAbc<-=D*&0cig*XFFgM)_c3{VLmUH4IRka$I!%HXg`)6^ktHSs}$zN?FyN2
zO@7Pentu+*^OpSn45i&1@PEZEjeW3xvBbXRD*v$O<9>XON6I(RMbUM{?St~yhd&rO
zE9idf%Bo}GSs3jZv{mnMC-C!uHUfJ9X`5|r3B3sCESc61_kYoLLB8~BH5e&pV6*yW
zZNvIW^jjgVcazdY92;2CI@BZlR!Cc%z!99G>nh4D?E=0m!H?6DmXzOG-a3S`doI1+
zz#O&#%7zWfJ7)D3VueI`Yp>Ms+CTdP9)H8@_QE`#b$~d^IxgmXXMEq~{29dOeC|`E
z7TclU+@XIyVaF_Y#k@VK0dbWeZk+!#?3Yg4HwEpxapeuA@c8`p_6W59jCFWF9@|Bz
z3tA7vZmVc3;m=OF;ZaSLPuzNPs*Oz~c2A*fAIQ%;@HwnGk7izy;|%-d?J)_zr`fu_
zPvqHAG|w3Pdof%-^s$1>EBGkWw%KN(Y8rWkv=S#;L7H*=h2z`Dtpl53T<-(SsXt!9
zaTbwRI2YCqOL>KJw`%>dUgQbk<APyhEWwv0xT(4-mf#iYaN*uLLN7vE&WJUXfBXFB
zBfut6-Vkk5iq|&D6AAwY>ST4NH8oDVmadZi`?=ECes+D{9s4((50yb<2*+K`*ok>~
z_Sb6E&beH2uWFdzV2>K;xC8gM=VEL>-&U*!`)p1{3*289?w*bKp2=PCevSDoQ5x)A
zRj&KBn|R!Yds8URvkNA*m+<P(_I|uk!ka;Pa^{pwJ}>;;tvpn9wS><n?A_+&B>PRc
zBac;*@))L<XJyPMUq%(KiAsUX7kPzuP+==5dQs#C#@L;@U}y_tJHxTaOUJQ(7W2Ws
z7n`t{S7}<y(qC~rSDH5RN-eM*M0uZn&BXRan(wz`Z>c!;k*ysm|7Jv+a)hpgGFpWP
z5xhd$^mYk^e*<ZUN^~K3g|tr3atQkhX%}uNDPA4FF7i0;Z-sfy+2Oed-IHRPS5wr^
z{#?`IYcX#w8!90FZg88=)xf+p5Bw1wZ_8btauFYQNS)`2{2S(BQVGoKy%ugL{|2t>
z13s?5*b>$UrL$8%pTPNn5zwWb2R4-O$Z<7}{ej96H-_oi&|PwzVg9u1CgFKL_m_**
z{x)Lg$D~S*r!eD_YoL0H+gA2f{X|^8$SdLkZv}-{s24ncu#rs^6Oawa;|tP49roby
zLev9r{A!&()H)2GQ=WL<1=?KP^b^|>yn@YR=kxYN)B|9rA*Lj?uW<gy*1I50A(jRI
z_VTMm=mALE*LEhwtKZP#6t683@jDkpdDS(3z^1W3q01?T?|udh8}mV0<53Gd4{cnH
z^}xu+me?OpOY}$WY~$OFU4;9e?YLO9zmx4WCl}k-8VTsVGNy#@_8wL7@kZt5BOY^^
z+*p2|<*l6o?Y~m0x*fxMp~s#h=zKlf_>2wa9j>cjiutbExIp4RE0opCmyqy<;@FOH
znK&<h0yFaHZHYZiQ~o?J5nV^z?3BJ^>PybQs#N<PlJHxCT~>D#&JSDwqre7i1&vo|
zH(0-es%F#!kk-dtn+5d+HeiF_8kG`!27|~j{D#;Q+#{chALs3VC;~A{f`?zdj}dWf
zDDQ{reJQ({HNP6g;q9h#_PQMVin-a*a@20P-d?BuXurDe1E;mPzd(8DlFXPoyxs7=
z)&;fCaW>|+YuIkN%=Scft(foW>Q^vFeEtDS_w8#W?Y5D1k7+GwXJ=*g`j&ZIWLx;g
ze~iZ*K^;KniCaNyR~R=J3`~Z)8`~AM+Ugufd_Q6v!tvn`M-uC6p#8_x_Q3uj+!uVu
z0@9k+TL)u=(f@_C@n1Qt^F%uY<vAWN#hAALTU7>(rAAKBPldHbU1)29lcK|~5&kda
zi#fLsVt_=xYrhVs;)1r5MpJRYl5_7-c1YcCnrC{Al6c&7dFk95u5mV}C*sAQTi=#{
z&-;DVAUtkbI@QE>pw!M|==fFE`L7?aT?rYA*5@d)S)aWsY<K>gh2q|ZOwRSy930oT
zsnHP~k6_o9PXgO5Y+KosbFi*V+!iRCH7=Pc?jb{^EaI_4!ebhHbL?UXkI8I{2c7fw
z4Zm<L-gKAPDTZx6GE;KCqq1AuD4ZX7g|+w4mar8RUPZeByuP??*oCTQY-c#eE&ho8
zMlm1!d-0+@wnNgi@fWp}&I>p^0{S{pUZvFDxV@z3`hB=V={)y0X#}s3e|LwCgkJ(_
zRs3uSKN`}aTAfSZT>m4sS9ebRyc^oT?$i^g9jg0Iy>b@w(YY_o<L5Fvga5|$8FB&M
z@1Mp+PxuMjtK#ip9)C0U^h}q$aSYkFOcxa2F>Vaw?Ua$n6Z+1{jbq7q`^Yc#^`4nw
z%x+l0HB5LQ83&Iltpa&JqcHHXX-o@>53gn)C_e12(R?hf5l8V+dl=2fqDcmdkM74x
zgO5sZG<#hgijQ|os!_Tspix7LkG4k}WMtIk`FI#<kNK!B@R4-!H0I;Z^jOTtK@HD`
z^Tr~m-KTLI4)c8MwnI7{@v(Heln;hk@BXud4+GQc<8uiQleyt{Z6x~&rGFDkN&fZR
z)0L&ujl7`s0@J(j@9`G~KCU17v=h~xXeTc5J;g`yn=~Iwd(wPV;AlQ_C)0d1y-4$s
z<CaSCp&wyKjCWuweBL*p_;5bdAVXD$=OcIJ`CVW?Dhqt<8gvTt(RM1&$IfV;k49Y_
zF&`WM;Q1I)mgi$;Fv-VpPm+(0wl5?+Oy+7h^YMLw0cG~7S9$hBv7Wm%gyiFMKpr0j
zSq}jh@ZK-{3pxbp4$$O=XH^Da{zW|mY3^;D@c4rC68<I<=p5g7N3qTo^$_Tm^O|r%
z4?)_;sY|?}y`*|*!s;8ud&KClqST%lL>vLqf~|KFdKl8~4v!`DFr@u<?h&Pj9;ar*
zT)zUCf(`QhaqT`4M}V{r_NP42{Sf(5xDbyLe<GcM<_%`8nGH5p@vby{m!THd;|G2o
ze?uEs-~NjG{N)UeyKJe2)^{rQvZvRK#P-tm<aCrjnH{(4YX;muyY3x2K8zb<wGEG7
zCu%|5Hk`BXYmf88HIUw62DQ*;^1tElc6Q`e@bAQ}I~yJ*S&xk7WnC?EB*$BEITKTG
zefTpbu<s^kNq9|RA3a<r$zPGP3h~0cgFS<`ENF2AzV&!NDtAF`D(<CjnM2vL2CBxC
z9;$Ju6BS3eno!)!bR27WJe;yq4~tF(n?%^r4Ov5BY%_8L^?c|*&BOZgDa?)ft2K^4
zHTOA<{j&O3mSa1`w~K*UF@m3Wo7(;cYL9BZZJiopKWz7^$!I^9$vAgAj|=qum&AI?
zJiBDr$X&7|<|&!b4xJEB;$~njH;5wI6&QrApy*uS4eA88#MIwL>4u!GNvQwiJzw};
zc@WvIkk6%u2Cv(a+NQsIwI=Kfw9S=qwOytD7Nm7gv?uflTqAIb6J=j^Pb};1b(U|}
z3cdGZfBR9-Ww>2$Z&*zD+fT;w?Rs<#i`v81H%-fWz<s_skc9S^vg?n0kmy%y-)%3f
z-Qc?X#we4opmEN)%}^ezW-YM?diJ;EH+WtVo*&p$_<ka61*Ki#xxxnh>ZsowN}sy_
zeGA9^_+0$opAMe|ElTt+=1YwXxJPNe0TVYuA0qPg{`3R(52X2O4ctQcC7K}@Jxu#+
z{cW+td<m4XKe8+_j|^%3AMEk~PT{w>Wo@XQAssg$J-M`1dicDhxc~oIZwS`0ehDkR
z(ANUF&8zp~{@r5sW7NLIxLF^6#r4LGhy0kyUyAYV>~R6*|HPe*or&`^FM)^m?7Wrl
zasI`DcTvA~R>obGu0MRlHY&YEVjpri|GCod^K@1|4TAR##O)^gm(Rky{OI~`%UDS`
z%Vi$rkn5!3USTUJoQd`WVmNa1ca^w^EU2&8UXU--wFu@+YAfFOL=p3M=oCYa`#7+@
zM0>y0Y^ON;+*1i__>KACdfcIE)cjq`>ovfp5c$+mR+OFT`L-9KW1#NMz0P?^bqu7r
z?yu=(%437;*+g6i@?C56+<iyCahONz%8jwz`tj&yWQRDe$D^U?P~Yk!(Rwg6e>b!L
z6>O(o)I;lP(EM?y7Yp(I9zMMf?Jr`t+~eamlPe*<6-SkRf%EYARH8gO-*ACTt5yS_
z4`nJ8*V$5?EG4|zDHC%AzVYz^?B@Z$XW*asPnz<N6#o0EeA)ozx_*4ziQjitS}re+
z>LG4P%2PX1B<G*tf>s^Ex(B!@=y4rwl!DSRd)nNmbd1$ROG?N1|2UiS+necIf~_#}
z1#Msaupe$8_$_W#B5H%SA@W&FI6&#0IUO7bUg7+qm8VgD+3LO9JlFPsxU-}0zLJ-*
zy<2qz&1ayvPE46BtaqGRLi{+FDRKKIuFt3$X#New6-PB5jQL`p`Jnx)T>VxR(_x(C
zHv_ZzjC4MMVX`k<OYBu!?$?*8lKpJ-U5KKY;@Jwr39jm;NX$2%c2wE&@LW_6{yorw
zK5qKm-$sp_RvC|}adURqHEP_v*?%UbbKkND;n@=H-nv3D{QN~W;NLFAyohyLkjAAP
zpytccACS5U^3~c|34ApL{1&&4jrzmdYT~-1+BPTrGRWJfOOof#Y8x;|nUCjUj?(U-
zeKc-1IhupV!K4Qe?<vNeX|My=d)bIp==h)9!S-?Z__Hh*bbNr)aq5Z;;Ap%LtbexP
zwhX<6^F!N%f5nZjD&gcEH`Qu|B>rb$rWyXmobdT`nS0~DNI1)7o;bPXosaxGjk<!w
z-_o<nW+6t-!2d6(>j=OO`2RhE;%wCYM-*ob7So*dnmB{vtamG#vy8?QDb8F**C)nJ
zU?BTw4#io`XEbLAPSKpH>(HF#yk1Srhrl&7`b@(AhqS-0_RTQWarS<J9=!z~%YW*E
zc?^5N^EkUa&!a<+9jKj)aYK9ZJl-41^Emr<Eaq`%HqT?q7@o(~Yco*(_N==<KR=RY
zht}1g_l>*xl=3jzJ;OWhU6)jn$4MlQz8gp$zf_m<=*pg~Hbug(f$6z(X$H?S{ACy?
z8&?Uxsq8H87MO1sHw!wi4@Wywyv_@tdEK<1=2ib{I>l>JW180vEq|nVeKjNl=4uH$
zcGHFC^~p<`*Q-Z-U@Rr<;;~6(DV_JVq$|biuFsypCUM<myX#UqZ-26FMrDClros=H
z*JTfRUeC|lk9p+IS|Hwvaq00quOH)iUhN;m;N$W4A?`gu*>(iat8EeRW8bqs^elqM
zZRav05GT&cH+Pp{`wBFnRpngki^~aKZ%mi+s!+B#S6#weHWM)8jl`b5V!Na7l;N`Q
zABL$kN@AbUI-GF_iT4DUXFg9b&xJwfImP@*#osSixJK!`;Kj7gTlE{Q^G3aB4sAv7
z(AF~^w-4Adaq}*wqjX-lvnQqVDokwUCG|_-{1leiYszc+{R!!x{dt}Dhs$Xke=jZQ
zyonFDW1Tl@E7+Y}Ce`vcT%Y($uzu8^3)jZu{xqgP_!(C@&Fc#3Mtg_sk$W?k7Zx`I
z(|mjf2_J1Z#RUh+elFwrBYHo@xb5S{w|1297r}bOcPlh}?C|)N;=}s+6^f66OKCnF
zU(tLFJVx`Oxk38@FVpZ`9l_C=-Ulf@);Fj900&<j3nlDXnHSqU>j`{B_ML(G_;{H2
z1Dd_shWYTX&-(#ZC3rqw&E@@o7BhH0+#d6Oz}WLrKG6D=+oT`ha7Q{{*On`?e1(LM
zY^HQW(hnG`mBvYrDs5lq`2hvpPaHinj^cx<O7n4L8O=x8&om$Ln`l0E-=z5%kxuiG
z9ZvJnwi(Sw&DJy@&abz5&iCW($KzTZFdwf4K5RIik6HD2KGZfmA8qIHd>mQD^I<FS
zaVMSRW8oc=kFYl+AIH~|eB7^3@^QBh$w%5Bd3+RfKk?{^`V=2?*@u*V?`V0Q@)P6l
zO{4TsZdF<jl?$c)#6f?0QhwsC+WRT}zWhC{ht~d0>-T3>X#M`Bp)2Jl#tcpJOsUHI
ziFHPo!W^A`%<G(yyRxy4(Ld$=L}nweb7t#!ofBO*8Xxz{;dQxtG_P}pd+~l^)la0K
zcx|XehajDE?`?`?oG~yZf062(T;|{hQkTcrOLciN`(;>V596?f)?<d~^8Cbt&Y5le
ziyf%$#CQ=<pXO|i4b55O6EtVx4m4*i!)eYgyr(&vXG?R&{z-GTtJF*?-rp-)L&YOr
z^rJcZJS@p`roh?uU59sqUa@$>b2ccI=WM0G*@$gCXFdXFexIW-XNFrfkxm()R7CNd
zg$SJWERu`$5YGa`^fuw_{4J8RN{gkODU{>)Yl-o0*#tH-kE>+%mlY&u9|z}gR*>g+
zL5J?iT1|1b>P!Nj9}~4L{QF^Rb(k9>cwA*uin3=eiayjjrQHu_?LodAp<n!OID(Hx
zls7tv{Qow=b&t(C<*~;V>0A`=tnzL$=HjUV#tTQ^{$skiOLeVN1%5uI(U3`A@Ex6u
zvQM!NiVcVN4Q$zZhE`Z7<F-TZTTi^A$97xfqP(p%Ud}M1-fASeSHX7evL16#82q59
z6&k8tUvIcX>D+#)w2moWehwAy9+pV!m~bWS2OaN6`$0}iXg|nqD(wfYp5{&YL0+p9
z(&u*Ib<FjxEN=gYf{v+Xw-vW<<;}bw^h;@8$6UF<`#~j7@;YW_5bp;~pC{EZ3}a|T
z`a$(hlYY?B##JT#K9_NIB>kY4C#y-urwI19pgcdQp!fUVeym0DVLcqa%TM;xp)&ox
zc&;tg?{kXM{eHwOy5FC^PWSt4nSTFp;VF-zZhXI=`m8u^_v1pp?`zkc==Xcd^ZkC9
z(C>F1e}cJi7y7;b7_#3F`HAfJ>r0aT{)tJypWCDG^!vqY?{7y<NZ8dWTDspKmg)ED
z73qFodbmu#zeW2md+*Wyi)IY%zeF^p{THnR?Z2e{xy^Hs(C;?{XYBwx|48WfOMl;j
z+t<D>@4x(1hVS?91^>nMJm2rPKH~jb)eLFBH!zp(k^al8A4*F4d0Vb%4(Y!n)+POy
zu%@K{Qv9#N<G=V7TTbzD@XrU7|8m!!)|D$4(z<eNWm;GEjiPns+IO_BEPW%J@?Q)e
zXkD36iPn`?QM9f+lSS)F>x3lF;exJw+;jrwXpo>QYYpRdW$|ac|B{ix>&j(uy#JEE
zj@Ol$g07rDkk^$h1zowYB&jQdhmiiul%1rmY_OEnmG>`@x^mojQdc&5N9xMbBl2`*
zL5`z<{b7m@pg6k|wvHNK+?+0^o9fEkV@deEJkWpQ=6dN9Xn4Y|xq4L30J|XOfq$(!
z*Qe$UCOMpiG$LOuM@M&4{TZWAg4isPPoZ1jG0klV)}NC%xMO~*9tK{j`-Ur~;c@7#
zML%Rea+&K#H{<%0>)?Ri7j*D-{5u5Osm;&P_XkiMf8&<(dHNH@VS8<nyw`;unPsI?
zIF5>{fVLE+L)5Q%`$*4LjkS{avj%2&WQatc<}!*3qY8~a-8ix$#YY)GdYrOeLF>~>
zRp@cbbuc|nt&|z3{2$Td)C6uKWryl?97L>x2DWDPqxGqBMM8QfVVsH|{%Je#cu^Rq
zk~8^n>TMl<oZ2IdQz35XJwg<xuXmXrrw$7Gv{y1YPL;S%j#E$UrQ?(ZHz`&n(Vw%}
zWfgo;x#G5u>$HN@rvv)s>C=Kf@3`m9jcw>oi2h#hH9bxxSE9!$>)G@;RZV7`+B$%q
zcf1oq&pYZa(&N;6nQ_Xq3O!C;iKNG=(AM<4;}|qPn$9~`n@!I<t{iKdF;W=Md^_yI
zyu}OS*>W8}o{c`o&pTGn;>WYe!g#i489$yK7RED97|*gT_<2X45&XQP!ik@E^t?dM
zJKAg^$Fn$-@htQ*IiB?+#<N%KsIla{qf$CvqIpMd6*=#i?wmL8SkV2cgB#{hyiT_n
zO^tW9GXB)deY8LI*^>6B>Td78+jJc3IQkg1?)JTmKh<~XDG#OKPc1$^1ap%k_){m7
zNPj9w@TWTYF86{s%G7DRKUGYOql}aKQ{{b6FfKT*z*`<?WrZhe^2RMR&iTG0<0$^U
z^8BfS-mV$dI#cah%Z_f>5;E;NbuZnn6|LxYO=?H`$$e$~<PS3KIuo@kC$#IE=*GBR
zj|lA=H<fJHzCye16#Qf+nQvEx(5_xYyW0CsJ*gw&WBw+7ayyfD9V%(pf~-&BJ>Oo9
z?WlHL?n&#9nlk$1tBn2_q@(pm8J3QZmD14hu?p+y_}E36_*lDFAF24*tmldhUqOG&
z@q4vRsy`-d<@Lw$O?-UpuAo1b3-PhFS9tx=|9AMl%2n>#WU2mO7~9rld~EU+GCt<%
zM#jf(NaJIM^W2Q8=Op^XS=s*fWo#D;L;UpN)ooi%^~WoBnvdEtd{p_7)~79H_$VvG
zhp!ADelmPqmEps(G95?Jec0wH@-gVvT!N3PTX;SW3w%5h_(&D_xGeCIBE(TPnD9~B
zgpb`Od}vJg_?_V61h=_98AsV6iK7&B`|-l_7mAOmGJMpL;iHxeAB|-A$dvJ4?mVXb
zm-FN4IGe3Zob78Rnh!nVgA?qBwqGLV<GSF#9N*0IaYyi99t(Vwn$NEjxNpM8N`emq
zQ_aMG@vJ2EU)pll4w7-U7AA4FG!s5{79u{BmJ=vG+|1;op$s3j%;e*t3?Cjow12xn
z#=i~dLHoD6QWMfeJ|g=DVLpBr_!wux#}k2%zJh=ITHs@!;NLFEhYyC}!-5Oekp68M
zd(yuhw3zg7pZCr4ZwtDv9I!5g;$v=QT30G$bY<P$w61I>qbtu0q5XxXGXBEfGP?30
z(v|H5UAbzv7jE}mg0Ac`m(-O#O#B6960a+Z3c9j8p)1S#CYC1sg-?%3f1#s^u3S+_
zbS3D8D$_bp?dqRM$31V>qT`;!H_>s=B{FeOJDIp=&rWpQvxZFEvwLGY?m12-?m1Gw
zz+<ft_sl*~54V3sA?`WQo{xJ*TJmwvWFhWpFUCF3@Nv%tLfo_HRx<ACY7+O<RV3q{
zha<_j=Z_=ExaUoixaY8ng(vR$XKr(fk0du*SJso!4IVP%LRpz{AxlO#yptIh9?R&4
z;xfA7jf`#>hI9if=!RMkDqudI2;;)*O}uW%6?DThVO%IF=my)Xyx*}>(3R6n#)ax8
zy1}0q7us^qOmu^@iEfx}q8s)W65Rmy<C9$tijSo-_T#FI{b(R#KbFeakJ2*sqpOVl
zaFnqhBW3Kzcp3XK4%v^Dg8ew}S`711S+E})P3*@c!G4q%?8l<hy#1Ib*bfU6`_an8
ze#DsAk3%N*!_&lm{AOZ5CKMw3k#wyz#fO)f_JftNA2u@fqr8k?+E2zWT_od|-jMN2
zU&`2z;mCe4g8gu<@M0^(EnW!rW2<04jtYLMXg`(+erY8W`;kQ04~DTb@k>vc_@(Pj
z{L<Sde(6*b`>{`AKMK08>{Q{)7Sp&zogZmk`DF{eo^SsyT35D~(Uohpw63gcrmj4V
zbY&YsS4O5^!0o<W(3Q*Pk-D;*pex%6ap?II$#`X;iLMN`CUxbze01gdLZT}nUO92r
zW2#-P&FuH>Wct08nf+cR)9+WA+3%mp^!t&Let&3X4sQQ9LcgCV^!p><==Y8${eE0N
z{r;>;zu%ruzn^5%@6#pyz97e=pufAQFVTFAq5X~vGP+^^M%wR4k<ksMWOPFZ8Qt(=
zV>Nfvd8+;Py{UOBn@;_x^%esY*6&>^=!R|=w_rX*-B7$D?|0}0zhk_h8(KDjc`66r
zr>A(`u(byIZV*~;VP&ElTAJvF2&rz!F6XQDw3Mu`sKlmZw3N(aWiv^Uu9Ec@Da_bM
z({OydFvPP*R?eaLxb145-{B`?KP=3&AE7e#W22e&<H<MdhmW8e9%e1ae7qOzN7y&)
z$6`S@)HSgmWAd>d7fkHOzI^P*ghFaRV0@`kYZJxCX*2ogD8q-sOg_S8_}Kan_(+h9
zFLU3_#C-fI@bR<2hdAHyT<}XpJ{p+tVaSJ%OD23|<-^B#6FxEu$@l_%_|{CJ_{cJo
zk4`dte2t^$OXd8I2pK+hn90Xu8T$czi1y>Ic0A_eFM*Gr^5LVg2_K{L;p4IiAN%v+
zW88Q6DCmC2`X)0eKEBHM9iL?Uj>$59hpUX=F<MElljtt9PC_o8eNN(c#C_1>cHb)a
z9o^@Xen(fq@5m9>Nw}N%9lZ#@!`^pP4!KUEt;sqG(|GnqiQiGs*Wm@*kEPo6%yW7j
z-p`fkb$A=6)9dhFSEAR8S5VRG@X}<~;Z;0GufxlbS%-JuvNH8uq+cr0@4Hq{EJl5I
z@KekM>brv%Z#00ldBnP4ja8}iNMRjb>hRu}rzBw=-j!H>9o|r39o`XP9o|r39bSz^
z{5rfz!h5mRgmrimp2Bx!-?KA?b$I2ATVNe)YqAc{Ya_W1Zw9drFPEuT;;ZC+hFm7G
zy!5@;&dQ`lxu{%myUDI;wpo(jz}!&r-&5vu<T94lPt)OdVbHm!mkp$Noo(hg)lFuc
z`Xn<>$;H?0p3w91MJCYm@)k1j^@raWr@RH7+i*OG`T8u3Q?-S0>ZTB17j=w{5MOU;
zGER*o#wi118eb1KiLWaTk@ND6P2%f`-x;S0vY!k(W|Lb#ijS#g^3nZY=A-Dp#7BB>
zSIoy3fe*)g_-G~Yu}YYK`A_*M^1qmmpF=xSd`vKtj~+67e3Y>taymC!M(5_3sdF_i
z>2-mV(Yip<e!NL*Oz=_V8#;H9;3u~h`1n~^7dV2jA9Q^EhKbHS`CXlRp1a~et_yT8
zMC$^5=W!GthJTq4bH^8pf60Ehey&OIQ6V4u;c7CzkbLAnz7);Jei#bz_;TWUD~gZd
zX7cg#zidAanrS~C<fA{n45&o#VV95na1;1gEsQTDANkvl)8DlpC%Dny;iI7YQ<*sp
zDLxL!_)~#0{#5Ee@Tb<u_){hSWq<03%zI5yGVe7R+BK&9sjyGJ>4OA+>Zh7zFmICt
zf9jOrPYo9QsbePoRH<+HQ#rzWO`<<F&TTL9bDWhWP5i0m|Hz+u#hx{JugRHsuZdxp
zFuP3A+d}^;*VT2x^9qH*pVIGgq<D=s)1LK|v1fn%13h%aOnY{(JH3u|4qC@5>Y-LI
ztT0~+;d_e3^08+gf;}50tYaPiAL^mA-?L|mecTTw>sZf9*0C0Jf2zf{3KSn2Gx-RV
z;p2l0ALi;ID>L<w+;}$%#f7~De_LVrYYVJLDI)MuG#@?WDexisQ^N>8^4CL_`RJih
zCgWXZA(}Vn?^BZEBjjJ^!(4yrn3?t?KR())e?;){c_aBAjTny+{VA{S@{zwDI{!WU
zfxf%{Jw6J$9_nyaLGh7crXE^srXI4Fi7&5~(L+{d>LKe)`uo!JHqqagHdha=okhRr
zJsG{{Jy6g?XEQEi-X;rr=%}EF^d@>}h!9`45cE*M1OEHcVto0apoeA&@#W4={CnOu
zCVHsJclD4$S^SvE_odH}-<STr9?E9!tR&y_o*{Y9yP$uUk$d%QGa4F*?-HcT@Y+j8
zzyD$;uk)kn@8^JyMr&$_>lQVW*LyPGCCHKaF2ULh^!Ia8(f4yi4)4SrA~-xEa9Bn7
ze$H`0mx~-05jZ?1d~ZPHu)6U5oK>aB@8=M@8GZk=Q9c}wxI%t!z@PZuKr*|_s)}Si
zkDe_(GVl921>G*rKK|gp=4_FfoSADE&E@Q$%)5P+nRmM&Gw-HC^KK%K!@Fh6@~9K+
zqA8DxZ}^E5g?Ts8E>;re-AwJ`_j&x!=iSzt%)4DTnRk0%qHxT+fjwNjDwpDQrOf)n
zGcxNB>&UD>TxsU|LwA|=hgD?WTlib%y@d%f?=Ad--dk8GtUuh)Vjt#9Tz{A(tUpW=
z)*mLCeDCSWN%Fmg68Wq@>?2)&h`#rfZSvm2YLoXCem8k<VT0tog@V35q)*~?ijVCM
z^tyDp^&x#^)`z&stPhD9M6XM)Zsxl5OOo{=@%B4$yNl~Xo_=F}h*DUW{(J(zF8xaw
z|DD<1#QKo(zAl#Jy7ZU%tV`b_Sszl+{r_G1i&VRIGt<B8E#v?HDdYc}>))L+)4x;6
z%$H3<^JSv{|GeZD-2N7V|Nk-{|Bey-yY9k#*-*m&&)>hh^j-h%Ja^V)zRax<&6gdI
zI8E`<#Y{f>n8}B^@u3nj@u8wJ>oM-j%!f$hL!XOmAozG8@bRtn7)lfWpX4L|_)syE
z_)sI0^%x0-G(H5np}6KK#m71`b%Udsx}ju9ar|9I_=caj6-#MIeJ4^*H+=ptbc1uz
zHH2=MD(Hsn$OFh9LF=(hbVKfUb%TK^yXrQcFF?-=ZRq>;R%Imnv~EZ<(G9o0qZ<mk
zAN02-hvH+enf~^If8YnLl8Fx~%=EX-^@EO@IbSB{2L(y|pudZzV&25~&>_Ju|CS&0
zX`%f3!viMqp(=tOWNi{3YVcjZJU>6^6?^Wx^JNCc)DQZjkoZBczHIfNbc)xG|DVRY
zq2Ba&Uk=KA_vMz%eA!GiUnc6IAj>7hc=zNR<DK~37giYWh70p$|JitF!BveQzxz_l
z<hw6rOy<i@OXkZ8di?ODVHd^69y9IPJTvW?x$(oVXaC*x)SL5(A9jDbfUr{s^NAmR
z{Dz&XCd3a{=Mz7y|BvicGMn+8_+df!%OdA(r8w*G5A4u;8NbY2-EI9Z>F!PE=MZ-2
z(KqanxDHyhL*hE5A%tI+zwR#n4|I1ykH;L?@GHf~2{Yp{J!IlB9y0M5`+xAhjx-*V
zx_1U{_btNvI$ypKk2xT`uXEQV9@B@2$JqOx+5extuOp4e6!dm2aVCvw*Hiy;yH@y@
z+I7N)WTIUa3*_I!65I7oKJ9wyAGB*hx91jbR#5HQ&P;pWS0;`kXV1-zvz?WRv)z>W
z?#sP=;wVLzCE@nB6yj|6^NF)@g07Ue=lRFkuA0Qz?wEY{W#o6_C<R?t4ymw=;$x?o
zx^nKntSdj8sVn^-m8IU(vpeQP{r>{DenVGkg!K`3XO6=hO%c{d<m96({}gm(aVsnI
zJ%<5GabDV7U0LtDx-y%&(D)C@`*aGW>v`#ViDWjb5bMg0oflD@`Tomx$Xs1%W2Uam
z&kivQ445A)!4BR1hOQL9U+4Q>JCwh!ERm0{{GJ^u=;PG2DRU`4xPO@sbH}OkW{y++
z^O+CQcn>4^xbuy1YN7D{l*orTA4K{c`HxfAzB^8x=S~;m`Jh`zW>9>v1)Ps>*$+=)
zy>PXTTFgf=!G7E}laK#a$9$iU6I@}nA82yJu*5Q%;$yd&^Fd|JoDY)wj+L9tIuiFy
z^mnW_oB189O6WUQ3xstfR{b=Xk1E3VFBb~)LCGfTNNNk;u{t8m2dxvnW0l`JlHSsF
zB<MR<n@zrBH7lR*Sa}QIvBJ|!|M#cBJOOw=2sVg0z!nocP#vPz#H-uz`-%}Yqg7Gr
zn(j5@)Zy+r?O;`$I#eAO7ZX>r5hMjg#^`iGv8p&#R8990HFY7XNOe$bj4o)1S`!|j
zN9VcJOh_0}Gg7UJi&n=$o^Un#p$W-5Ngb^UMrWyq#-j8nb+ld;88lEA6CI>O`>III
zaFt#Y6OD>;M%N6F9UP<yMLUgMguPf*xH?Fu84i_%9MM52kIuL=FecczqmPJFtKekF
z7pIC2jfo1<=~a3-wM8?Orc<lou<>^gs#1_fua1*eAs*E!6rB_lrdH_($En5Qjp_Jt
zsL@&ckpxuhI8~?y-C0m@OpFd4z|SFAAE#Ca>El$I=)8v!Jva*QL`JG3(J?ht4em4+
zJ$Frr9zA#WnySJ27@QOnqDD_&KP(n<g{s3;gCq6m04_I5t&fO-n^6x{g+S`ySg16d
zA08JoBq$^%GD<Z_9oHx}Zg8|Z?>Ktu+Hd4RHzL3gj_Zz2(#5JnG+`QbXpph^Fjb^Z
zEx8<Oaq0Eo*2Qa^-h51~J}6Wjty4qoP$dvMa5uyQQboo_sL(NJ!VpzRggOYFh4Z5Q
zm`I%}Di*;MJS<Wjujb1j)1zZT#b+wbE<9@ICas+D)~p38UwEWJp_(}86&ONHGCC$u
zD=-j*?s0IeCOTZGnOcwQ*rYjMnhU@cu8NA{Q=9Rr&dnhe9!_jbq$Xq-IyY1utB)9>
z(LsY~q5(X7UGzMnb@)N(fhlw_QWX^(3Z(%YxK8NeL5NehIcMU!QL3Rq!5Zj5&04lX
zxnUob7ltmWH=ZG+hpHp>D%2;`u~3XL5mgH9Lv`U~bh&sV^^l-Ly*ng=e+DR@i!(kG
zVI2~oi44uN1-Jl|tc#7*=&|X5t2B{5j;NUE7=27M5FowddiBw@<J4iOw?)A9!{9PF
zDLhC@1U5<1N2430)}yMaV{u<>;@r%Q-=HeOG2FRPdDsA;zKie!L!pa^iNv<TSU;iF
zoZ-U!EvQkSAFSegr8-ij(<8eUt=2aZ?m`m+IR^*xP~s{lAfovmhx)<)p^dCO+0f{L
z{U6$e6>WeU+afe-Mj<;JnK!Nlt5CPng~Y`1_NgWAOQ^A7ybD1+M;t_9U$CjDzqr8w
zAeLy-TZ}_#P2*^Uz66S;glM;+dj_F_5XlWx7#O8c+;7p2FoqiS4oadF4!SmfGOApk
zevN8MGXE>G2$dg?L;@aH`nWW5Zq%$_g0}H^ZIiCrrV-Wwfu)fK3s&p&c?v}9>=zPf
zCniVZfj&|brO|6${6Yr@2il@TQeC5M=GPz)zAF|T1Ug9DJRq<<+LJS~+7<zU716P8
zj5^wu0fDfPOA{3v6Q@^2hae+~bceQ8ApGx)!_g3}ZH=$Q3pA~3K;RGPfQ%;6x=jj1
z%UBe+)z!Knt$PS+^w?od0FEY6NWy4TadE0)HbH36#e=}$5WS7ogU@9X9m*fodip8G
zYrVK4!CLQ$TA!|3rk-CBzoO%{N+Dw?)XzrC2Eu!`8dohhDQTkCx2v{IJwJ;;(7m48
zwgCYF9bma0{^O_6Yug1+;^6t>O%%u4_ImA4!GSg?5t%E16{_9AuV^5Af*1`)TECE?
z;h0Bs6H&1$y-i>{7L=a9Dp(!aCOQQ5g*Y3nfBi&l#{_LagnNWX1g?Ik2vqmZUA0|=
lx_6CeBX|97dTsY$T`+C{v3KZ@;T#;T*Y@zU9vs}{{{bCry#N3J

literal 0
HcmV?d00001

diff --git a/Experiments/Shallow/Experiment1/xgboost_0poslabel.py b/Experiments/Shallow/Experiment1/xgboost_0poslabel.py
new file mode 100644
index 0000000..4aaec44
--- /dev/null
+++ b/Experiments/Shallow/Experiment1/xgboost_0poslabel.py
@@ -0,0 +1,32 @@
+import pandas as pd
+import time
+from models_hyperparams import models_to_test, non_probabilistic_models_to_test
+from models_hyperparams import hyperparameters_per_model as hyperparameters
+from cross_validation import LearningModelCrossVal
+
+
+if __name__ == '__main__':
+    training_data_path = '../input/feature_extraction_train_updated.csv'
+    testing_data_path = '../input/feature_extraction_test_updated.csv'
+
+    train_df = pd.read_csv(training_data_path, encoding='latin-1')
+    test_df = pd.read_csv(testing_data_path, encoding='latin-1')
+
+    cols_drop = ['article_title', 'article_content', 'source', 'source_category', 'unit_id']
+    lm = LearningModelCrossVal(train_df, test_df, output_folder='output_xgboost_poslabel0/',
+                               cols_drop=cols_drop,
+                               over_sample=False,
+                               standard_scaling=True,
+                               minmax_scaling=False,
+                               learning_curve=False)
+
+    for model in models_to_test:
+        model_name = models_to_test[model]
+        print('\n********** Results for %s **********' % model_name)
+        t0 = time.time()
+        lm.cross_validation(model, hyperparameters[model_name], model_name, 10,
+                            lm.test_df, 10, probabilistic=True, pos_class_label=0)
+        t1 = time.time()
+        print('function took %.3f min\n' % (float(t1 - t0) / 60))
+
+    print('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
\ No newline at end of file