10591035
32117
VAIBHAV JAISWAL
10101
Supervised Classification
19162
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.tree._classes.DecisionTreeClassifier)(1)
8304396
Python_3.7.7. Sklearn_1.0.2. NumPy_1.21.6. SciPy_1.7.3.
copy
true
19075
with_mean
true
19075
with_std
true
19075
add_indicator
false
19084
copy
true
19084
fill_value
null
19084
missing_values
NaN
19084
strategy
"mean"
19084
verbose
0
19084
ccp_alpha
0.0
19085
class_weight
null
19085
criterion
"gini"
19085
max_depth
null
19085
max_features
null
19085
max_leaf_nodes
null
19085
min_impurity_decrease
0.0
19085
min_samples_leaf
1
19085
min_samples_split
2
19085
min_weight_fraction_leaf
0.0
19085
random_state
47361
19085
splitter
"best"
19085
memory
null
19156
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "scaler", "step_name": "scaler"}}]
19156
verbose
false
19156
memory
null
19162
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numerical", "step_name": "numerical"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "model", "step_name": "model"}}]
19162
verbose
false
19162
openml-python
Sklearn_1.0.2.
1464
blood-transfusion-service-center
https://www.openml.org/data/download/1586225/php0iVrYT
-1
22109666
description
https://api.openml.org/data/download/22109666/description.xml
-1
22109667
predictions
https://api.openml.org/data/download/22109667/predictions.arff
area_under_roc_curve
0.6016164005519417 [0.601616,0.601616]
average_cost
0
f_measure
0.7074724504273251 [0.820119,0.346749]
kappa
0.16925635843018347
kb_relative_information_score
0.07565846298434355
mean_absolute_error
0.30244322156413145
mean_prior_absolute_error
0.3630445632798566
weighted_recall
0.7179144385026738 [0.84386,0.314607]
number_of_instances
748 [570,178]
precision
0.6997612894406816 [0.797678,0.386207]
predictive_accuracy
0.7179144385026739
prior_entropy
0.7916465694609683
relative_absolute_error
0.8330746474531006
root_mean_prior_squared_error
0.4258399633559147
root_mean_squared_error
0.5149108264558916
root_relative_squared_error
1.2091651107567187
total_cost
0
unweighted_recall
0.5792331953479204 [0.84386,0.314607]
area_under_roc_curve
0.5399610136452242 [0.539961,0.539961]
area_under_roc_curve
0.5745614035087719 [0.574561,0.574561]
area_under_roc_curve
0.6038011695906433 [0.603801,0.603801]
area_under_roc_curve
0.6549707602339181 [0.654971,0.654971]
area_under_roc_curve
0.6798245614035088 [0.679825,0.679825]
area_under_roc_curve
0.5974658869395711 [0.597466,0.597466]
area_under_roc_curve
0.5960038986354775 [0.596004,0.596004]
area_under_roc_curve
0.5653021442495126 [0.565302,0.565302]
area_under_roc_curve
0.6986584107327142 [0.698658,0.698658]
area_under_roc_curve
0.5294117647058822 [0.529412,0.529412]
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
f_measure
0.6364223602484471 [0.765217,0.228571]
f_measure
0.7137127371273713 [0.845528,0.296296]
f_measure
0.6750447275684467 [0.806723,0.258065]
f_measure
0.7441490683229813 [0.834783,0.457143]
f_measure
0.8048305084745763 [0.881356,0.5625]
f_measure
0.6654237288135593 [0.79661,0.25]
f_measure
0.7211864406779661 [0.830508,0.375]
f_measure
0.7108624708624709 [0.820513,0.363636]
f_measure
0.7567567567567568 [0.842105,0.470588]
f_measure
0.6406978098788444 [0.775862,0.1875]
kappa
-0.005961251862891171
kappa
0.16225749559082905
kappa
0.07108239095315017
kappa
0.29210134128166926
kappa
0.4462025316455696
kappa
0.05063291139240509
kappa
0.20886075949367064
kappa
0.18604651162790684
kappa
0.3126934984520125
kappa
-0.03552206673842816
kb_relative_information_score
-0.1536747487596714
kb_relative_information_score
0.18559942615805458
kb_relative_information_score
0.030315152196524465
kb_relative_information_score
0.16008703538777275
kb_relative_information_score
0.29697463015965486
kb_relative_information_score
0.012351265638081066
kb_relative_information_score
0.09483793828074268
kb_relative_information_score
0.04718791985022002
kb_relative_information_score
0.206811415963828
kb_relative_information_score
-0.1263619141614493
mean_absolute_error
0.37491882447054853
mean_absolute_error
0.27308702408702396
mean_absolute_error
0.3213492063492063
mean_absolute_error
0.2812115483083224
mean_absolute_error
0.23257142857142862
mean_absolute_error
0.3206349206349207
mean_absolute_error
0.2917261904761904
mean_absolute_error
0.3161898025346302
mean_absolute_error
0.2549990450725744
mean_absolute_error
0.35785039847539846
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.35873873873873896
mean_prior_absolute_error
0.35873873873873896
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
74 [57,17]
number_of_instances
74 [57,17]
precision
0.6330223123732251 [0.758621,0.235294]
precision
0.7054545454545454 [0.787879,0.444444]
precision
0.6622332506203473 [0.774194,0.307692]
precision
0.7419066937119675 [0.827586,0.470588]
precision
0.8021545667447306 [0.852459,0.642857]
precision
0.6541451990632319 [0.770492,0.285714]
precision
0.7133489461358313 [0.803279,0.428571]
precision
0.7040000000000001 [0.8,0.4]
precision
0.7567567567567568 [0.842105,0.470588]
precision
0.6334402198808977 [0.762712,0.2]
predictive_accuracy
0.64
predictive_accuracy
0.7466666666666667
predictive_accuracy
0.6933333333333332
predictive_accuracy
0.7466666666666667
predictive_accuracy
0.8133333333333332
predictive_accuracy
0.68
predictive_accuracy
0.7333333333333333
predictive_accuracy
0.72
predictive_accuracy
0.7567567567567568
predictive_accuracy
0.6486486486486487
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7778597106646706
prior_entropy
0.7778597106646706
relative_absolute_error
1.0296950283906228
relative_absolute_error
0.750019291289248
relative_absolute_error
0.8825688617324761
relative_absolute_error
0.772332873997516
relative_absolute_error
0.6387453179601998
relative_absolute_error
0.8806071132129428
relative_absolute_error
0.8012107911862556
relative_absolute_error
0.8683988278195859
relative_absolute_error
0.7108210447778941
relative_absolute_error
0.9975237124753694
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4207539065176338
root_mean_prior_squared_error
0.4207539065176338
root_mean_squared_error
0.586311660874269
root_mean_squared_error
0.48333718988926244
root_mean_squared_error
0.5229725094627986
root_mean_squared_error
0.48894955809790663
root_mean_squared_error
0.43914367299652607
root_mean_squared_error
0.5245126893045486
root_mean_squared_error
0.5179053260353756
root_mean_squared_error
0.516209888147743
root_mean_squared_error
0.47668841773673304
root_mean_squared_error
0.5760875706263181
root_relative_squared_error
1.372821266703529
root_relative_squared_error
1.1317113705009403
root_relative_squared_error
1.2245156131148518
root_relative_squared_error
1.1448524675446332
root_relative_squared_error
1.0282343225597421
root_relative_squared_error
1.2281218720082017
root_relative_squared_error
1.212651040677249
root_relative_squared_error
1.2086812523482122
root_relative_squared_error
1.1329387804905742
root_relative_squared_error
1.3691793746950613
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
unweighted_recall
0.49707602339181284 [0.77193,0.222222]
unweighted_recall
0.567251461988304 [0.912281,0.222222]
unweighted_recall
0.5321637426900585 [0.842105,0.222222]
unweighted_recall
0.6432748538011696 [0.842105,0.444444]
unweighted_recall
0.706140350877193 [0.912281,0.5]
unweighted_recall
0.5233918128654971 [0.824561,0.222222]
unweighted_recall
0.5964912280701754 [0.859649,0.333333]
unweighted_recall
0.587719298245614 [0.842105,0.333333]
unweighted_recall
0.6563467492260062 [0.842105,0.470588]
unweighted_recall
0.48297213622291024 [0.789474,0.176471]
usercpu_time_millis
0
usercpu_time_millis
0
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
0
usercpu_time_millis
0
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis
15.625
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
15.625
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_testing
15.625
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
15.625
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
0
usercpu_time_millis_training
15.625
usercpu_time_millis_training
15.625
usercpu_time_millis_training
15.625
usercpu_time_millis_training
0
wall_clock_time_millis
8.99505615234375
wall_clock_time_millis
10.01596450805664
wall_clock_time_millis
9.97304916381836
wall_clock_time_millis
9.992837905883789
wall_clock_time_millis
9.973764419555664
wall_clock_time_millis
11.014938354492188
wall_clock_time_millis
12.972831726074219
wall_clock_time_millis
9.994268417358398
wall_clock_time_millis
10.974884033203125
wall_clock_time_millis
10.994195938110352
wall_clock_time_millis_testing
2.9990673065185547
wall_clock_time_millis_testing
1.9993782043457031
wall_clock_time_millis_testing
1.9974708557128906
wall_clock_time_millis_testing
2.998828887939453
wall_clock_time_millis_testing
2.0008087158203125
wall_clock_time_millis_testing
1.9977092742919922
wall_clock_time_millis_testing
1.9996166229248047
wall_clock_time_millis_testing
1.9998550415039062
wall_clock_time_millis_testing
1.9996166229248047
wall_clock_time_millis_testing
3.9975643157958984
wall_clock_time_millis_training
5.995988845825195
wall_clock_time_millis_training
8.016586303710938
wall_clock_time_millis_training
7.975578308105469
wall_clock_time_millis_training
6.994009017944336
wall_clock_time_millis_training
7.972955703735352
wall_clock_time_millis_training
9.017229080200195
wall_clock_time_millis_training
10.973215103149414
wall_clock_time_millis_training
7.994413375854492
wall_clock_time_millis_training
8.97526741027832
wall_clock_time_millis_training
6.996631622314453
weighted_recall
0.64 [0.77193,0.222222]
weighted_recall
0.7466666666666667 [0.912281,0.222222]
weighted_recall
0.6933333333333334 [0.842105,0.222222]
weighted_recall
0.7466666666666667 [0.842105,0.444444]
weighted_recall
0.8133333333333334 [0.912281,0.5]
weighted_recall
0.68 [0.824561,0.222222]
weighted_recall
0.7333333333333333 [0.859649,0.333333]
weighted_recall
0.72 [0.842105,0.333333]
weighted_recall
0.7567567567567568 [0.842105,0.470588]
weighted_recall
0.6486486486486487 [0.789474,0.176471]