target,target_name,model,family,is_baseline,task,n_folds,notes,mae,mae_sd,rmse,rmse_sd,median_ae,median_ae_sd,r2,r2_sd,poisson_deviance,poisson_deviance_sd,mae_minutes,mae_minutes_sd,status,fit_seconds,pinball_loss,pinball_loss_sd,pr_auc,pr_auc_sd,roc_auc,roc_auc_sd,brier,brier_sd,f1_best,f1_best_sd,threshold_best,threshold_best_sd,prevalence,prevalence_sd,macro_f1,accuracy,macro_f1_english,macro_f1_kannada,n_classes
B1,clearance_duration,mean,baseline,True,regression,5,training mean; absolute floor,1.260522106664037,0.24065851165191923,1.7509625051756554,0.3123877691892465,0.8182186930855149,0.10365072055742873,-0.03382723196245516,0.046237587712695025,0.690449950536684,0.212962633001905,554.9495030799408,326.5441776584073,ok,0.0,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,ridge,linear,False,regression,5,L2 linear; interpretable reference,1.2027714447584033,0.22107559382787254,1.558701342695872,0.26439943382884573,0.9284125467194627,0.16692183551890266,0.17806096764552876,0.06060978670652946,0.5400559881078847,0.1506640444624086,554.24205262534,321.0496104169942,ok,0.0,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,poisson_glm,linear,False,regression,5,principled for counts; log link matches the data-generating process,1.2004740738582493,0.226246960403613,1.5670191250666126,0.27521093954153764,0.9107688574864687,0.15149816303053437,0.17034943702382183,0.06249915395863155,0.5445168447346016,0.15971452782463025,555.4238921566173,321.414740670501,ok,0.1,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,random_forest,trees,False,regression,5,best performer in the NYC parking-ticket literature,1.154109403970058,0.20386322571261686,1.5038677747309048,0.24884664840166593,0.8994341603897524,0.16931014891016072,0.2349544148863924,0.04191577024976812,0.5034028656508378,0.1336955141062254,546.6246740710304,318.3372895885935,ok,0.5,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,extra_trees,trees,False,regression,5,variance-reduced contrast to random forest,1.170107417853491,0.196936582044114,1.517832248851376,0.22795257951879677,0.916624274822818,0.18568561664998787,0.21698979131712245,0.06127465914212488,0.5084229745354177,0.12182766493882241,551.1426573705972,316.830673070478,ok,0.3,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,hist_gbm,gbdt,False,regression,5,sklearn-native GBDT; no extra dependency,1.1611349606244405,0.17240512322910476,1.5410742439131884,0.21841018429659834,0.8821463162595204,0.11817623056696008,0.1886687817938532,0.09343934368444978,0.5321782898307907,0.11978398454851363,549.0341083921994,303.80459511948555,ok,3.6,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,hist_gbm_poisson,gbdt,False,regression,5,GBDT with a Poisson objective; regularised to keep the log link stable,1.1868588555401016,0.21445214888247693,1.5547732119350581,0.2727403476151118,0.9004333603032701,0.14198654381520903,0.18322617151449858,0.06898591271113204,0.5362677504652243,0.1518549175604013,552.7475898758667,320.23679844832895,ok,0.9,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,xgboost,gbdt,False,regression,5,GBDT benchmark with a count objective,1.1191195132282084,0.18446061055021115,1.4936198240242242,0.23736234194795164,0.8383735278704563,0.10175839466304133,0.24277048434229717,0.06488679791559139,0.49897152893099894,0.12794040677529817,538.6806482810352,310.529315461345,ok,1.2,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,lightgbm,gbdt,False,regression,5,fast GBDT; also supplies quantile regression for module B,1.1645695314531896,0.20544872614182955,1.5196092073161651,0.2507225683803128,0.8932175105056505,0.171521305785665,0.2176992125048928,0.06449326836308021,0.5118820240103862,0.13289145525794557,549.3335062251077,320.4921936535713,ok,0.7,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,catboost,gbdt,False,regression,5,ordered target statistics for high-cardinality categoricals,1.174484044419622,0.1534538387857054,1.557109600189331,0.2101488036586489,0.8907565744051299,0.08694029233256124,0.172111730452497,0.07541396133765116,0.5468205776648352,0.11220804648294296,538.7609414365767,312.3461617908101,ok,1.9,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,torch_mlp,deep,False,regression,5,"feedforward net, Poisson NLL, on mps",4.051738410161095,2.0251186137000228,10.668206192627903,9.935947712074,2.0321815146253757,0.6175151979876022,-54.39175130074419,90.93946061170031,4.404505914031806,3.908198617112085,14098.059535723452,7892.800038703403,ok,1.0,,,,,,,,,,,,,,,,,,,
B1,clearance_duration,lightgbm_q50,quantile,False,regression,5,LightGBM quantile regression at P50,,,,,,,,,,,541.7571322286803,,ok,,0.5658338191196254,0.09038348141031136,,,,,,,,,,,,,,,,,
B1,clearance_duration,lightgbm_q90,quantile,False,regression,5,LightGBM quantile regression at P90,,,,,,,,,,,895.5332533083016,,ok,,0.23434683692192348,0.04018826495735153,,,,,,,,,,,,,,,,,
B2,road_closure,prior,baseline,True,classification,5,training prevalence for every row,,,,,,,,,,,,,ok,0.0,,,0.0872716303646841,0.015447408075374954,0.5,0.0,0.0797543279072396,0.013092340418834492,0.16023722561204323,0.02604840552371711,0.07779003473865542,0.003531587336180356,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,logistic,linear,False,classification,5,interpretable reference,,,,,,,,,,,,,ok,0.1,,,0.3304267858760782,0.06471350802192852,0.7584314260669237,0.04641625426463492,0.07129412959900527,0.015619908442937083,0.38178201640419,0.04937322041037473,0.20804403607236194,0.14745539082543763,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,random_forest,trees,False,classification,5,,,,,,,,,,,,,,ok,0.7,,,0.35779048369341504,0.07988578135872054,0.7723327586297549,0.044824833846754765,0.07123508605190483,0.01345000678288648,0.4326232448515889,0.07302480797017939,0.1953908651352837,0.04965092516914378,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,extra_trees,trees,False,classification,5,,,,,,,,,,,,,,ok,0.5,,,0.3024126443474463,0.08285502431502986,0.7443135887736125,0.04988927394341682,0.07340695542256745,0.01399431883063253,0.38827682438344857,0.05921573087401412,0.17721072629847961,0.055056346149816346,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,hist_gbm,gbdt,False,classification,5,,,,,,,,,,,,,,ok,7.2,,,0.3268907537929864,0.0607311114359096,0.7365730144984709,0.05000068175392363,0.07237993687219586,0.013179333444799383,0.385491439170347,0.06543762427594003,0.14926429545520192,0.11864230225770306,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,xgboost,gbdt,False,classification,5,,,,,,,,,,,,,,ok,1.4,,,0.3445279383603258,0.08145351326476695,0.7564887454692879,0.039417263136213306,0.07034847421374624,0.014451926365461434,0.40934629190793936,0.0803790517207043,0.1640516385436058,0.06275346045375635,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,lightgbm,gbdt,False,classification,5,,,,,,,,,,,,,,ok,5.6,,,0.34713162813596854,0.05956817136956174,0.7582920185954402,0.037401106139839,0.07459904815861046,0.017229342835227944,0.41444885495934836,0.0649962113608353,0.05424631594083251,0.06795915052012211,0.0872716303646841,0.015447408075374954,,,,,
B2,road_closure,catboost,gbdt,False,classification,5,,,,,,,,,,,,,,ok,2.6,,,0.36154124887172945,0.07135973584030703,0.7684213052775986,0.04496009015012284,0.06880849046861276,0.01507502042241341,0.4322953764133743,0.06712787868962242,0.18886126651494797,0.08503831960200346,0.0872716303646841,0.015447408075374954,,,,,
B3,priority,prior,baseline,True,classification,5,training prevalence for every row,,,,,,,,,,,,,ok,0.0,,,0.6145971416089371,0.02353481658298647,0.5,0.0,0.23695592363446677,0.005439595310225961,0.7610913675212618,0.017970121630957004,0.6162612661577086,0.002386558743819849,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,logistic,linear,False,classification,5,interpretable reference,,,,,,,,,,,,,ok,0.1,,,0.9933935255657236,0.008031403033504112,0.9950780370164105,0.006034972026040526,0.006008575093313115,0.007661646948506368,0.9974926982551462,0.003481571668642841,0.7476996574894341,0.3411055493181163,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,random_forest,trees,False,classification,5,,,,,,,,,,,,,,ok,0.5,,,0.9973889310065299,0.004981379764173996,0.9979504925338165,0.003571257954802564,0.039381992777994576,0.020561213204744477,0.9974926982551462,0.003481571668642841,0.507360591280179,0.034660868112138456,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,extra_trees,trees,False,classification,5,,,,,,,,,,,,,,ok,0.4,,,0.9972109556737389,0.004959056524694404,0.9977295869448346,0.003401513231123668,0.07302468713917501,0.022180478049269765,0.9974926982551462,0.003481571668642841,0.6170408971335138,0.07512827299533618,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,hist_gbm,gbdt,False,classification,5,,,,,,,,,,,,,,ok,2.5,,,0.9997690883722552,0.0004909861818297587,0.9996994001036444,0.0006276316772815197,0.0032002353687849983,0.004188334085885902,0.9985050903771393,0.0018159116197732246,0.8086935859415953,0.4260624958457399,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,xgboost,gbdt,False,classification,5,,,,,,,,,,,,,,ok,0.8,,,0.9993561268804145,0.0014355424114520315,0.9991910133372957,0.0018013747447878274,0.002776907357935806,0.0042633603214508485,0.9981519545757035,0.003704339551672374,0.8368383288383484,0.1871354260488693,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,lightgbm,gbdt,False,classification,5,,,,,,,,,,,,,,ok,3.3,,,0.9997107195995196,0.0006426535470423078,0.9996955843868814,0.0006731356339959261,0.0015704390192494478,0.002348312161142105,0.9991597127597821,0.001475565546121307,0.8499869811010715,0.33359256431401246,0.6145971416089371,0.02353481658298647,,,,,
B3,priority,catboost,gbdt,False,classification,5,,,,,,,,,,,,,,ok,2.5,,,0.9998711193264042,0.0002839992804634838,0.9998204267084283,0.0003939978795279536,0.0022089023102066473,0.0030789153217137236,0.9989900799351055,0.0018465461649882862,0.9303915652402834,0.11580199387046292,0.6145971416089371,0.02353481658298647,,,,,
B4,cause_from_text,majority,baseline,True,classification,1,always predict the most common cause,,,,,,,,,,,,,ok,,,,,,,,,,,,,,,,0.04407376233835795,,,,
B4,cause_from_text,tfidf_char_logreg,nlp,False,classification,1,TF-IDF char n-grams (2-5) into logistic regression; handles code-mixed English/Kannada without tokenisation,,,,,,,,,,,,,ok,,,,,,,,,,,,,,,,0.4781960734643766,0.6555423122765197,0.48334516832814006,0.47172455632110644,12.0