6055580
1
Jan van Rijn
9956
Supervised Classification
6952
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
4090233
axis
0
6947
categorical_features
[]
6947
copy
true
6947
fill_empty
0
6947
missing_values
"NaN"
6947
strategy
"mean"
6947
strategy_nominal
"most_frequent"
6947
verbose
0
6947
categorical_features
[]
6948
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
6948
handle_unknown
"ignore"
6948
n_values
"auto"
6948
sparse
true
6948
threshold
0.0
6949
C
5631.441808630022
6953
cache_size
200
6953
class_weight
null
6953
coef0
0.635260932508428
6953
decision_function_shape
null
6953
degree
3
6953
gamma
0.00013333113867289485
6953
kernel
"sigmoid"
6953
max_iter
-1
6953
probability
true
6953
random_state
1193
6953
shrinking
false
6953
tol
0.00020033370389570157
6953
verbose
false
6953
openml-pimp
openml-python
Sklearn_0.18.1.
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
13034310
description
https://api.openml.org/data/download/13034310/description.xml
-1
13034311
predictions
https://api.openml.org/data/download/13034311/predictions.arff
area_under_roc_curve
0.3558491233184621 [0.176641,0.360826,0.350442,0.189672,0.367104,0.356917,0.343414,0.300774,0.326398,0.352614,0.352298,0.690264,0.326003,0.158639,0.39865,0.303853,0.270728,0.356601,0.290193,0.27515,0.175142,0.473508,0.165706,0.335202,0.420088,0.29193,0.211387,0.385779,0.977337,0.976271,0.386845,0.982549,0.433315,0.123973,0.232944,0.367538,0.343533,0.555946,0.358536,0.287468,0.315106,0.988392,0.292285,0.364735,0.401808,0.330346,0.357352,0.232154,0.339585,0.334413,0.147505,0.318343,0.335913,0.324345,0.346494,0.991946,0.979469,0.306183,0.317593,0.327819,0.119157,0.44433,0.311473,0.345073,0.355496,0.204991,0.327266,0.358497,0.329912,0.360905,0.326319,0.339032,0.079003,0.148018,0.128751,0.105733,0.334886,0.157336,0.358812,0.314158,0.377645,0.357944,0.356996,0.321383,0.145886,0.06479,0.372907,0.108694,0.336545,0.988906,0.651808,0.295523,0.219441,0.57091,0.09831,0.337374,0.318936,0.31633,0.329951,0.170325]
average_cost
0
kappa
0.026618040870792562
kb_relative_information_score
28.891990834852955
mean_absolute_error
0.019772469892301234
mean_prior_absolute_error
0.019799992711748222
number_of_instances
1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16]
predictive_accuracy
0.03627267041901188
prior_entropy
6.6438309601245775
recall
0.03627267041901188 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.375,0,0.375,0,0,0,0,0,0,0,0,0,0.1875,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5625,0.375,0,0,0.0625,0,0.0625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0.25,0,0,0,0.125,0,0]
relative_absolute_error
0.9986099581021232
root_mean_prior_squared_error
0.09949872432040595
root_mean_squared_error
0.09939405795482248
root_relative_squared_error
0.9989480632410279
total_cost
0
area_under_roc_curve
0.208615456571929 [0.056962,0.050314,0.220126,0.018987,0.031646,0.167722,0.151899,0.18239,0.03481,0.110759,0.031447,0.96519,0.03481,0.018987,0.25,0.018987,0.053797,0.09434,0.018987,0.018987,0.106918,0.262658,0.025316,0.075949,0.129747,0.031447,0.314465,0.050633,1,0.943396,0.088608,0.993671,0.163522,0.534591,0.72327,0.075949,0.100629,0.968553,0.044304,0.344937,0.018987,1,0.031447,0.047468,0.194969,0.025157,0.107595,0.09434,0.082278,0.079114,0.761006,0.018987,0.050314,0.047468,0.056604,0.993671,0.996835,0.069182,0.031447,1,0.050314,0.208861,0.025157,1,0.050633,0.018987,0.050633,0.09434,0.08805,0.063291,0.047468,0.03481,0.327044,0.496855,0.012658,0.028481,0.044304,0.031646,0.031447,0.025157,0.106918,0.031646,0.025316,0.03481,0.106918,0.018987,0.177215,0.031646,0.079114,0.993671,0.202532,0.053797,0.056604,0.78481,0.028481,0.066456,0.056604,1,0.031646,0.955975]
area_under_roc_curve
0.2081666467637926 [0.079114,0.257862,0.037736,0.009494,0.022152,0.053797,0.050633,0.044025,0.028481,0.094937,0.044025,0.468354,0.006329,0.006329,0.094937,0.009494,0.031646,0.09434,0.006329,0.107595,0.050633,0.085443,0.031646,0.031646,0.193038,0.088608,0.748428,0.018987,1,1,0.082278,0.984177,0.150943,0.371069,0.786164,0.047468,0.119497,0.949686,0.037975,0.218354,0.012658,0.987421,0.289308,0.14557,0.09434,0.031447,0.120253,0.113208,0.022152,0.03481,0.72327,0.006329,0.025157,0.03481,0.018868,1,0.981132,0.113208,0.025157,1,0.056604,0.642405,0.018868,0.987421,0.091772,0.155063,0.044304,0.194969,0.062893,0.079114,0.022152,0.025316,0.238994,0.213836,0.009494,0.006329,0.012658,0.037975,0.025157,0.025157,0.031447,0.094937,0.490566,0.006329,0.119497,0.006329,0.06962,0.06962,0.031646,0.993671,0.946203,0.018987,0.062893,1,0.063291,0.098101,0.044025,0.993711,0.037975,0.974843]
area_under_roc_curve
0.1836890972056365 [0.091772,0.044025,0.031646,0.012658,0.047468,0.081761,0.060127,0.025157,0.056604,0.025316,0.025316,0.91195,0.037975,0.015823,0.082278,0.012658,0.037975,0.063291,0.015823,0.037736,0.037975,0.408228,0.063291,0.050314,0.144654,0.03481,0.18239,0.148734,1,0.996835,0.129747,1,0.066456,0.06962,0.10443,0.09434,0.050314,0.560127,0.044025,0.987421,0.041139,0.993711,0.062893,0.063291,0.136076,0.025316,0.063291,0.006329,0.031646,0.050314,0.641509,0.050633,0.041139,0.012658,0.169811,0.996835,1,0.18239,0.031447,0.981132,0.012658,0.993711,0.069182,0.943396,0.041139,0.015823,0.037975,0.09434,0.018868,0.155063,0.012658,0.129747,0.022152,0.176101,0.015823,0.028481,0.022152,0.836478,0.053797,0.079114,0.018868,0.234177,0.044025,0.012658,0.075472,0.044304,0.177215,0.213836,0.063291,0.974843,0.987421,0.120253,0.018987,1,0.022152,0.050314,0.062893,0.031646,0.025316,0.955975]
area_under_roc_curve
0.20554867247830585 [0.047468,0.113208,0.018987,0.012658,0.041139,0.119497,0.06962,0.101266,0.050314,0.053797,0.047468,0.993711,0.03481,0.012658,0.234177,0.018987,0.047468,0.072785,0.022152,0.056604,0.025316,0.316456,0.031646,0.176101,0.132075,0.022152,0.176101,0.335443,0.977848,0.990506,0.202532,0.993711,0.411392,0.025316,0.028481,0.320755,0.119497,0.566456,0.427673,0.993711,0.025316,0.993711,0.257862,0.107595,0.085443,0.047468,0.047468,0.031646,0.031447,0.044025,0.660377,0.018987,0.022152,0.056962,0.06962,0.993671,0.993711,0.069182,0.037736,1,0.012658,0.955975,0.037736,1,0.06962,0.924528,0.047468,0.062893,0.025157,0.060127,0.041139,0.120253,0.025316,0.163522,0.015823,0.012658,0.085443,0.993711,0.101266,0.025316,0.044025,0.047468,0.125786,0.037975,0.106918,0.047468,0.022152,0.106918,0.066456,0.993711,0.993711,0.075949,0.14557,1,0.415094,0.056604,0.132911,0.056962,0.053797,0.962264]
area_under_roc_curve
0.16847061340657601 [0.085443,0.094937,0.155063,0.031447,0.050314,0.056604,0.056604,0.237342,0.08805,0.119497,0.031646,0.91195,0.106918,0.006329,0.352201,0.031447,0.050633,0.107595,0.009494,0.037736,0.022152,0.025157,0.041139,0.138365,0.220126,0.041139,0.028481,0.044025,0.990506,1,0.100629,0.993711,0.126582,0.031646,0.075949,0.025157,0.050633,0.227848,0.075472,0.72327,0.018987,1,0.098101,0.113924,0.237342,0.079114,0.107595,0.056962,0.037736,0.08805,0.060127,0.018987,0.012658,0.050314,0.091772,0.987342,1,0.03481,0.018987,0.047468,0.009494,1,0.012658,0.009494,0.081761,0.924528,0.031646,0.047468,0.025316,0.066456,0.100629,0.050314,0.018987,0.047468,0.03481,0.050314,0.056604,0.880503,0.025316,0.015823,0.088608,0.044304,0.031447,0.050314,0.012658,0.015823,0.066456,0.232704,0.056962,0.993711,0.974843,0.132911,0.03481,1,0.188679,0.081761,0.158228,0.015823,0.060127,0.015823]
area_under_roc_curve
0.17829890136135668 [0.106918,0.079114,0.129747,0.100629,0.075472,0.150943,0.050314,0.037975,0.031447,0.106918,0.028481,0.987421,0.037736,0.009494,0.062893,0.037736,0.022152,0.110759,0.028481,0.037736,0.037975,0.36478,0.072785,0.09434,0.062893,0.047468,0.022152,0.062893,0.968354,0.996835,0.584906,1,0.287975,0.028481,0.079114,0.037736,0.028481,0.28481,0.069182,0.704403,0.012658,0.993671,0.060127,0.060127,0.246835,0.060127,0.031646,0.21519,0.044025,0.069182,0,0.044025,0.120253,0.056604,0.075949,0.990506,1,0.177215,0.015823,0.03481,0.009494,1,0.031646,0.031646,0.050314,0.899371,0.044304,0.075949,0.060127,0.079114,0.050314,0.069182,0.006329,0.037975,0.009494,0.081761,0.069182,0.893082,0.022152,0.047468,0.496835,0.08805,0.031646,0.050314,0.031646,0.012658,0.050633,0.169811,0.03481,0.993711,0.968553,0.037975,0.053797,0.18038,0.132075,0.106918,0.072785,0.072785,0.022152,0.012658]
area_under_roc_curve
0.1685586836239153 [0.132075,0.075949,0.037975,0.018868,0.037736,0.098101,0.044025,0.015823,0.044304,0.062893,0.170886,0.886076,0.044025,0.037736,0.044025,0.018868,0.018868,0.066456,0.018868,0.009494,0.056962,0.36478,0.509434,0.050633,0.167722,0.006329,0.142405,0.018868,1,0.984177,0.037736,0.987342,0.047468,0.015823,0.031646,0.094937,0.06962,0.351266,0.063291,0.009494,0.012579,1,0.018987,0.062893,0.28481,0.053797,0.037736,0.14557,0.025157,0.044304,0,0.018868,0.03481,0.100629,0.044304,0.987421,0.981013,0.117089,0.015823,0.022152,0.012658,0.300633,0.012658,0.164557,0.069182,0.874214,0.018868,0.075949,0.091772,0.09434,0.050314,0.018868,0.025316,0.155063,0.056604,0.044025,0.025157,0.028481,0.079114,0.018987,0.047468,0.018868,0.148734,0.031447,0.022152,0.245283,0.025157,0.015823,0.062893,1,0.822785,0.238994,0.009494,0.170886,0.27673,0.053797,0.012658,0.025316,0.031447,0.025316]
area_under_roc_curve
0.15211642186131666 [0.226415,0.025316,0.139241,0.025157,0.09434,0.132911,0.100629,0.018987,0.053797,0.201258,0.205696,0.003165,0.018868,0.069182,0.044025,0.018868,0.201258,0.151899,0.025157,0.126582,0.044025,0.427673,0.081761,0.015823,0.278481,0.08805,0.022152,0.314465,1,1,0.037736,0.990506,0.5,0,0.037975,0.243671,0.028481,0.78481,0.208861,0,0.018868,0.981013,0.056962,0.106918,0.088608,0.018987,0.012579,0.006329,0.031646,0.050633,0,0.012579,0.085443,0.031447,0.028481,0.987421,0.990506,0.056962,0,0.028481,0,0.012658,0,0.003165,0.025157,0.060127,0.037736,0.088608,0.006329,0.157233,0.031447,0.018868,0.003165,0.025316,0.018868,0.081761,0.031447,0.006329,0.294304,0.025316,0.009494,0.025157,0.028481,0.044025,0.037975,0.27044,0.415094,0.028481,0.012579,0.990506,0.161392,0.125786,0.028481,0.563291,0.053797,0.006329,0.015823,0.072785,0.012579,0.006329]
area_under_roc_curve
0.16592180160815226 [0.025157,0.094937,0.044025,0.041139,0.113924,0.072785,0.041139,0.132911,0.025316,0.06962,0.031447,0.060127,0.018987,0.113208,0.212025,0.025316,0.106918,0.113208,0.050314,0.003165,0.062893,0.170886,0.125786,0.053797,0.101266,0.037736,0.025316,0.14557,1,0.993711,0.041139,0.981013,0.069182,0.339623,0.937107,0.047468,0.06962,0.943396,0.037975,0.006329,0.044025,0.996835,0.009494,0.188679,0.056604,0.069182,0.050314,0.427673,0.208861,0.082278,0.015823,0.075472,0.031447,0.047468,0.047468,0.993711,0.990506,0.075949,0.025316,0.041139,0.075472,0.193038,0.028481,0.287975,0.14557,0.022152,0.044025,0.037975,0.03481,0.477987,0.025316,0.066456,0.301887,0.050633,0.044025,0.012658,0.047468,0.025316,0.044025,0.037736,0.208861,0.08805,0.155063,0.031646,0.037975,0.125786,0.037736,0.025316,0.050314,0.996835,0.294304,0.18239,0.09434,0.5,0.056962,0.050633,0.022152,0.930818,0.031447,0.03481]
area_under_roc_curve
0.18105859963885795 [0.14557,0.095541,0.018987,0.022293,0.39172,0.06051,0.063694,0.082278,0.025478,0.111465,0.037975,0.955414,0.015924,0.037975,0.047771,0.012739,0.018987,0.082278,0.025316,0.015924,0.031646,0.175159,0.28481,0.044586,0.375796,0.031646,0.012739,0.079618,1,1,0.197452,1,0.031646,0.335443,0.85443,0.038217,0.038217,0.962025,0.06051,0.025478,0.044304,0.987261,0.035032,0.253165,0.018987,0.037975,0.310127,0.398734,0.057325,0.070064,0.031847,0.015924,0.050633,0.022293,0.107595,1,0.996815,0.070064,0.025478,0.095541,0.025316,0.235669,0.012739,0.050955,0.070064,0.041401,0.031646,0.076433,0.038217,0.050633,0.022293,0.012739,0.234177,0.025478,0.025316,0.012739,0.019108,0.012739,0.025316,0.037975,0.019108,0.117834,0.057325,0.035032,0.012739,0.158228,0.050633,0.047771,0.044304,1,0.770701,0.246835,0.044304,0.646497,0.082803,0.063694,0.037975,1,0.018987,0.019108]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
kappa
0.020033982692535663
kappa
0.026702480644651604
kappa
0.026587129143128035
kappa
0.026702480644651604
kappa
0.0200727042832306
kappa
0.01984032882776065
kappa
0.038469141659747755
kappa
0.032449310303940555
kappa
0.014140137451615454
kappa
0.026413735142273978
kb_relative_information_score
3.059124956825409
kb_relative_information_score
2.8558803128291834
kb_relative_information_score
3.1146815204387877
kb_relative_information_score
3.2625545762523105
kb_relative_information_score
3.4866607155268166
kb_relative_information_score
3.262776069617755
kb_relative_information_score
2.7092819904381282
kb_relative_information_score
1.733148116349842
kb_relative_information_score
2.845654596061596
kb_relative_information_score
2.562227980513155
mean_absolute_error
0.01976834396692051
mean_absolute_error
0.01977761635216175
mean_absolute_error
0.019766070842826083
mean_absolute_error
0.01976410575677871
mean_absolute_error
0.01976880937201324
mean_absolute_error
0.019767588318685365
mean_absolute_error
0.01977652771014219
mean_absolute_error
0.019795423587235284
mean_absolute_error
0.01976869327770227
mean_absolute_error
0.01977151376273677
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.01980002942907591
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.019799955856386102
mean_prior_absolute_error
0.01979995631910742
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1]
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1]
number_of_instances
160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2]
number_of_instances
160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2]
number_of_instances
159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2]
predictive_accuracy
0.03125
predictive_accuracy
0.0375
predictive_accuracy
0.0375
predictive_accuracy
0.0375
predictive_accuracy
0.03125
predictive_accuracy
0.03125
predictive_accuracy
0.05
predictive_accuracy
0.04375
predictive_accuracy
0.025
predictive_accuracy
0.03773584905660377
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
recall
0.03125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0]
recall
0.0375 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0]
recall
0.0375 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0]
recall
0.0375 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0]
recall
0.03125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0]
recall
0.03125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
recall
0.05 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0.5,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
recall
0.04375 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
recall
0.025 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
recall
0.03773584905660377 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0]
relative_absolute_error
0.9983997265120788
relative_absolute_error
0.9988680281009452
relative_absolute_error
0.9982849224355209
relative_absolute_error
0.9981856758129635
relative_absolute_error
0.9984232317848567
relative_absolute_error
0.9983652722291153
relative_absolute_error
0.9988167576527023
relative_absolute_error
0.9997710970073024
relative_absolute_error
0.998421078364488
relative_absolute_error
0.9985635040849457
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.0994985414402977
root_mean_squared_error
0.09937418729191978
root_mean_squared_error
0.09941364883575521
root_mean_squared_error
0.09936432039706483
root_mean_squared_error
0.0993553000198087
root_mean_squared_error
0.09937826073648764
root_mean_squared_error
0.09936985835962213
root_mean_squared_error
0.09941184978523987
root_mean_squared_error
0.09950216736400823
root_mean_squared_error
0.09937946909486198
root_mean_squared_error
0.09939141955760736
root_relative_squared_error
0.9987465034408325
root_relative_squared_error
0.9991431062206894
root_relative_squared_error
0.9986473375809171
root_relative_squared_error
0.9985566795288636
root_relative_squared_error
0.9987874430311827
root_relative_squared_error
0.9987067070878305
root_relative_squared_error
0.9991287376622613
root_relative_squared_error
1.000036465349237
root_relative_squared_error
0.9988032988099336
root_relative_squared_error
0.9989233823818954
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
usercpu_time_millis
3338.4497599995484
usercpu_time_millis
3408.9442300000883
usercpu_time_millis
3062.891262999983
usercpu_time_millis
2836.0997730001145
usercpu_time_millis
2829.8615590001646
usercpu_time_millis
2842.2077970003556
usercpu_time_millis
2876.1581590001697
usercpu_time_millis
2848.5561860002235
usercpu_time_millis
2848.7730060001013
usercpu_time_millis
2837.0400419998987
usercpu_time_millis_testing
192.80768299995543
usercpu_time_millis_testing
191.42770700000256
usercpu_time_millis_testing
159.86821900014547
usercpu_time_millis_testing
159.73019400007615
usercpu_time_millis_testing
158.90774699983012
usercpu_time_millis_testing
167.66085200015368
usercpu_time_millis_testing
158.89607899998737
usercpu_time_millis_testing
161.78146699985518
usercpu_time_millis_testing
157.88788100007878
usercpu_time_millis_testing
157.63712799980567
usercpu_time_millis_training
3145.642076999593
usercpu_time_millis_training
3217.5165230000857
usercpu_time_millis_training
2903.0230439998377
usercpu_time_millis_training
2676.3695790000384
usercpu_time_millis_training
2670.9538120003344
usercpu_time_millis_training
2674.546945000202
usercpu_time_millis_training
2717.2620800001823
usercpu_time_millis_training
2686.7747190003683
usercpu_time_millis_training
2690.8851250000225
usercpu_time_millis_training
2679.402914000093