10591722
31244
Sharath Kumar Reddy Alijarla
3
Supervised Classification
18983
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)
8304495
Python_3.7.3. Sklearn_0.20.0. NumPy_1.21.5. SciPy_1.7.3.
n_jobs
null
18952
remainder
"passthrough"
18952
sparse_threshold
0.3
18952
transformer_weights
null
18952
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]}}]
18952
memory
null
18953
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
18953
axis
0
18954
copy
true
18954
missing_values
"NaN"
18954
strategy
"mean"
18954
verbose
0
18954
copy
true
18955
with_mean
true
18955
with_std
true
18955
memory
null
18956
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
18956
copy
true
18957
fill_value
-1
18957
missing_values
NaN
18957
strategy
"constant"
18957
verbose
0
18957
categorical_features
null
18958
categories
null
18958
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
18958
handle_unknown
"ignore"
18958
n_values
null
18958
sparse
true
18958
threshold
0.0
18959
class_weight
null
18971
criterion
"gini"
18971
max_depth
null
18971
max_features
1.0
18971
max_leaf_nodes
null
18971
min_impurity_decrease
0.0
18971
min_impurity_split
null
18971
min_samples_leaf
7
18971
min_samples_split
13
18971
min_weight_fraction_leaf
0.0
18971
presort
false
18971
random_state
0
18971
splitter
"best"
18971
memory
null
18983
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}]
18983
openml-python
Sklearn_0.20.0.
3
kr-vs-kp
https://www.openml.org/data/download/3/dataset_3_kr-vs-kp.arff
-1
22111577
description
https://api.openml.org/data/download/22111577/description.xml
-1
22111578
predictions
https://api.openml.org/data/download/22111578/predictions.arff
area_under_roc_curve
0.9981644558129423 [0.998164,0.998164]
average_cost
0
f_measure
0.9806002028555738 [0.981437,0.979685]
kappa
0.9611225931665138
kb_relative_information_score
0.9562742811615276
mean_absolute_error
0.022228701714778063
mean_prior_absolute_error
0.49901358092237413
weighted_recall
0.9806007509386734 [0.982025,0.979044]
number_of_instances
3196 [1669,1527]
precision
0.9806004243293541 [0.98085,0.980328]
predictive_accuracy
0.9806007509386734
prior_entropy
0.998575539213492
relative_absolute_error
0.04454528406559727
root_mean_prior_squared_error
0.49950623821173523
root_mean_squared_error
0.11129743810718898
root_relative_squared_error
0.22281491119238275
total_cost
0
unweighted_recall
0.9805345208260499 [0.982025,0.979044]
area_under_roc_curve
0.9964384955579038 [0.996438,0.996438]
area_under_roc_curve
0.9984540722476616 [0.998454,0.998454]
area_under_roc_curve
0.9956948847403233 [0.995695,0.995695]
area_under_roc_curve
0.9997847442370162 [0.999785,0.999785]
area_under_roc_curve
0.9999608625885484 [0.999961,0.999961]
area_under_roc_curve
0.9999608625885484 [0.999961,0.999961]
area_under_roc_curve
0.9992912827781715 [0.999291,0.999291]
area_under_roc_curve
0.9942286479672233 [0.994229,0.994229]
area_under_roc_curve
0.9989560352978255 [0.998956,0.998956]
area_under_roc_curve
0.9994090765836747 [0.999409,0.999409]
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
0.9874960839598999 [0.988095,0.986842]
f_measure
0.9687573345329369 [0.96988,0.967532]
f_measure
0.9749921679197996 [0.97619,0.973684]
f_measure
0.9843671959925964 [0.985163,0.983498]
f_measure
0.9874911830400878 [0.988166,0.986755]
f_measure
0.9968745412282848 [0.997015,0.996721]
f_measure
0.9811978818544379 [0.981707,0.980645]
f_measure
0.9686600603656251 [0.96988,0.96732]
f_measure
0.9749216300940439 [0.976048,0.973684]
f_measure
0.9811960362193749 [0.981928,0.980392]
kappa
0.9749383247836474
kappa
0.9374144337962057
kappa
0.9498766495672945
kappa
0.9686643164904034
kappa
0.9749245778317597
kappa
0.9937362981522079
kappa
0.9623584015103839
kappa
0.9372022520571675
kappa
0.9497321147179325
kappa
0.9623213512343006
kb_relative_information_score
0.9686351760221783
kb_relative_information_score
0.9386213276067827
kb_relative_information_score
0.9511012536173221
kb_relative_information_score
0.9638056061267296
kb_relative_information_score
0.9696234066158036
kb_relative_information_score
0.976244516417505
kb_relative_information_score
0.9577614769904791
kb_relative_information_score
0.9206177891885352
kb_relative_information_score
0.952207620896192
kb_relative_information_score
0.9640223836670241
mean_absolute_error
0.01599702380952381
mean_absolute_error
0.030372908341658338
mean_absolute_error
0.02478670634920635
mean_absolute_error
0.018845217282717285
mean_absolute_error
0.015941220238095237
mean_absolute_error
0.012875124007936509
mean_absolute_error
0.021195627778699877
mean_absolute_error
0.040711108814557084
mean_absolute_error
0.02351832249951372
mean_absolute_error
0.01808938188248533
mean_prior_absolute_error
0.4990286898061312
mean_prior_absolute_error
0.4990286898061312
mean_prior_absolute_error
0.4990286898061312
mean_prior_absolute_error
0.4990286898061312
mean_prior_absolute_error
0.4990286898061312
mean_prior_absolute_error
0.4990286898061312
mean_prior_absolute_error
0.49909524173611874
mean_prior_absolute_error
0.4989560481570598
mean_prior_absolute_error
0.4989560481570598
mean_prior_absolute_error
0.4989560481570598
number_of_instances
320 [167,153]
number_of_instances
320 [167,153]
number_of_instances
320 [167,153]
number_of_instances
320 [167,153]
number_of_instances
320 [167,153]
number_of_instances
320 [167,153]
number_of_instances
319 [166,153]
number_of_instances
319 [167,152]
number_of_instances
319 [167,152]
number_of_instances
319 [167,152]
precision
0.9875695560170854 [0.982249,0.993377]
precision
0.9688404203323557 [0.975758,0.96129]
precision
0.975060739057173 [0.970414,0.980132]
precision
0.984533088235294 [0.976471,0.993333]
precision
0.9877923976608187 [0.976608,1]
precision
0.9968936011904763 [0.994048,1]
precision
0.9815131572946932 [0.993827,0.968153]
precision
0.9687443173336591 [0.975758,0.961039]
precision
0.9749216300940439 [0.976048,0.973684]
precision
0.9812780740680426 [0.987879,0.974026]
predictive_accuracy
0.9875
predictive_accuracy
0.96875
predictive_accuracy
0.975
predictive_accuracy
0.984375
predictive_accuracy
0.9875
predictive_accuracy
0.996875
predictive_accuracy
0.9811912225705329
predictive_accuracy
0.9686520376175548
predictive_accuracy
0.974921630094044
predictive_accuracy
0.9811912225705329
prior_entropy
0.9986191629215038
prior_entropy
0.9986191629215038
prior_entropy
0.9986191629215038
prior_entropy
0.9986191629215038
prior_entropy
0.9986191629215038
prior_entropy
0.9986191629215038
prior_entropy
0.9988113175509788
prior_entropy
0.9984094255154751
prior_entropy
0.9984094255154751
prior_entropy
0.9984094255154751
relative_absolute_error
0.03205632088154798
relative_absolute_error
0.06086405243245229
relative_absolute_error
0.049669902463595414
relative_absolute_error
0.037763795284071755
relative_absolute_error
0.03194449650637978
relative_absolute_error
0.025800368337416425
relative_absolute_error
0.042468102290396936
relative_absolute_error
0.08159257506733773
relative_absolute_error
0.04713505846132302
relative_absolute_error
0.03625445958476729
root_mean_prior_squared_error
0.4995213618016774
root_mean_prior_squared_error
0.4995213618016774
root_mean_prior_squared_error
0.4995213618016774
root_mean_prior_squared_error
0.4995213618016774
root_mean_prior_squared_error
0.4995213618016774
root_mean_prior_squared_error
0.4995213618016774
root_mean_prior_squared_error
0.4995879730599906
root_mean_prior_squared_error
0.49944864525507615
root_mean_prior_squared_error
0.49944864525507615
root_mean_prior_squared_error
0.49944864525507615
root_mean_squared_error
0.09917794732328741
root_mean_squared_error
0.13956941134754106
root_mean_squared_error
0.12048232699723928
root_mean_squared_error
0.09348714221954435
root_mean_squared_error
0.08320634989239081
root_mean_squared_error
0.07030471353263473
root_mean_squared_error
0.108595070287216
root_mean_squared_error
0.14986162657010654
root_mean_squared_error
0.12597096085665507
root_mean_squared_error
0.09666609069894903
root_relative_squared_error
0.1985459580058231
root_relative_squared_error
0.27940629174324205
root_relative_squared_error
0.2411955447964882
root_relative_squared_error
0.18715344201167738
root_relative_squared_error
0.1665721553774628
root_relative_squared_error
0.140744158125809
root_relative_squared_error
0.21736926456028974
root_relative_squared_error
0.30005412567205964
root_relative_squared_error
0.2522200471528354
root_relative_squared_error
0.19354560597432427
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
0.9872020664553246 [0.994012,0.980392]
unweighted_recall
0.968964032718876 [0.964072,0.973856]
unweighted_recall
0.9746780947908105 [0.982036,0.96732]
unweighted_recall
0.9839340925991155 [0.994012,0.973856]
unweighted_recall
0.9869281045751634 [1,0.973856]
unweighted_recall
0.9967320261437909 [1,0.993464]
unweighted_recall
0.9816717851799355 [0.96988,0.993464]
unweighted_recall
0.9688780334068705 [0.964072,0.973684]
unweighted_recall
0.9748660573589663 [0.976048,0.973684]
unweighted_recall
0.9814450047273873 [0.976048,0.986842]
usercpu_time_millis
93.75
usercpu_time_millis
62.5
usercpu_time_millis
62.5
usercpu_time_millis
46.875
usercpu_time_millis
62.5
usercpu_time_millis
62.5
usercpu_time_millis
62.5
usercpu_time_millis
46.875
usercpu_time_millis
78.125
usercpu_time_millis
46.875
usercpu_time_millis_testing
15.625
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_testing
15.625
usercpu_time_millis_training
78.125
usercpu_time_millis_training
62.5
usercpu_time_millis_training
46.875
usercpu_time_millis_training
46.875
usercpu_time_millis_training
62.5
usercpu_time_millis_training
62.5
usercpu_time_millis_training
62.5
usercpu_time_millis_training
46.875
usercpu_time_millis_training
62.5
usercpu_time_millis_training
31.25
wall_clock_time_millis
281.2793254852295
wall_clock_time_millis
62.47353553771973
wall_clock_time_millis
62.506675720214844
wall_clock_time_millis
53.43508720397949
wall_clock_time_millis
62.506675720214844
wall_clock_time_millis
62.505483627319336
wall_clock_time_millis
62.51072883605957
wall_clock_time_millis
62.50429153442383
wall_clock_time_millis
78.13167572021484
wall_clock_time_millis
62.50739097595215
wall_clock_time_millis_testing
15.625715255737305
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
15.62643051147461
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
0
wall_clock_time_millis_testing
15.625953674316406
wall_clock_time_millis_testing
15.622854232788086
wall_clock_time_millis_training
265.6536102294922
wall_clock_time_millis_training
62.47353553771973
wall_clock_time_millis_training
46.880245208740234
wall_clock_time_millis_training
53.43508720397949
wall_clock_time_millis_training
62.506675720214844
wall_clock_time_millis_training
62.505483627319336
wall_clock_time_millis_training
62.51072883605957
wall_clock_time_millis_training
62.50429153442383
wall_clock_time_millis_training
62.50572204589844
wall_clock_time_millis_training
46.88453674316406
weighted_recall
0.9875 [0.994012,0.980392]
weighted_recall
0.96875 [0.964072,0.973856]
weighted_recall
0.975 [0.982036,0.96732]
weighted_recall
0.984375 [0.994012,0.973856]
weighted_recall
0.9875 [1,0.973856]
weighted_recall
0.996875 [1,0.993464]
weighted_recall
0.9811912225705329 [0.96988,0.993464]
weighted_recall
0.9686520376175548 [0.964072,0.973684]
weighted_recall
0.9749216300940439 [0.976048,0.973684]
weighted_recall
0.9811912225705329 [0.976048,0.986842]