9200270
3886
Benjamin Strang
3996
Supervised Classification
predictive_accuracy
7722
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.linear_model.stochastic_gradient.SGDClassifier))(1)
7130158
axis
0
7633
categorical_features
[]
7633
copy
true
7633
fill_empty
0
7633
missing_values
"NaN"
7633
strategy
"median"
7633
strategy_nominal
"most_frequent"
7633
verbose
0
7633
categorical_features
[]
7644
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7644
handle_unknown
"ignore"
7644
n_values
"auto"
7644
sparse
false
7644
threshold
0.0
7645
copy
true
7646
with_mean
true
7646
with_std
true
7646
cv
3
7722
error_score
"raise"
7722
fit_params
null
7722
iid
true
7722
n_iter
250
7722
n_jobs
-1
7722
param_distributions
{"classifier__alpha": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-07, "b": 0.1, "args": [], "kwds": {"base": 10, "low": 1e-07, "high": 0.1}}}, "classifier__penalty": ["l2", "l1", "elasticnet"], "classifier__tol": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-05, "b": 0.1, "args": [], "kwds": {"base": 10, "low": 1e-05, "high": 0.1}}}, "imputation__strategy": ["mean", "median", "most_frequent"]}
7722
pre_dispatch
"2*n_jobs"
7722
random_state
3
7722
refit
true
7722
return_train_score
"warn"
7722
scoring
null
7722
verbose
0
7722
memory
null
7723
alpha
0.0001
7724
average
false
7724
class_weight
null
7724
epsilon
0.1
7724
eta0
0.0
7724
fit_intercept
true
7724
l1_ratio
0.15
7724
learning_rate
"optimal"
7724
loss
"log"
7724
max_iter
2000
7724
n_iter
null
7724
n_jobs
1
7724
penalty
"l2"
7724
power_t
0.5
7724
random_state
3
7724
shuffle
true
7724
tol
null
7724
verbose
0
7724
warm_start
false
7724
openml-python
Sklearn_0.19.1.
study_123
1162
AP_Ovary_Uterus
https://www.openml.org/data/download/54045/AP_Ovary_Uterus.arff
-1
19326965
description
https://api.openml.org/data/download/19326965/description.xml
-1
19326966
predictions
https://api.openml.org/data/download/19326966/predictions.arff
area_under_roc_curve
0.8562629905547157 [0.85602,0.856651]
average_cost
0
f_measure
0.8639168431705235 [0.887179,0.826772]
kappa
0.714055057721805
kb_relative_information_score
226.29405613445874
mean_absolute_error
0.13764415835336627
mean_prior_absolute_error
0.47375584694425227
number_of_instances
322 [198,124]
precision
0.8650934663162925 [0.901042,0.807692]
predictive_accuracy
0.8633540372670808
prior_entropy
0.9620372403199735
recall
0.8633540372670807 [0.873737,0.846774]
relative_absolute_error
0.29053817328309006
root_mean_prior_squared_error
0.4866178408152876
root_mean_squared_error
0.3694439318271337
root_relative_squared_error
0.7592075358522844
total_cost
0
area_under_roc_curve
0.9692307692307691 [0.969231,0.969231]
area_under_roc_curve
0.9154428904428905 [0.894231,0.948077]
area_under_roc_curve
0.74765625 [0.75,0.74375]
area_under_roc_curve
0.9458333333333333 [0.945833,0.945833]
area_under_roc_curve
0.9692708333333334 [0.958333,0.9875]
area_under_roc_curve
0.7916666666666666 [0.791667,0.791667]
area_under_roc_curve
0.8549479166666667 [0.841667,0.877083]
area_under_roc_curve
0.8354166666666666 [0.841667,0.825]
area_under_roc_curve
0.9493927125506074 [0.949393,0.949393]
area_under_roc_curve
0.8041497975708503 [0.771255,0.852227]
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
0.9383116883116883 [0.952381,0.916667]
f_measure
0.908381374722838 [0.926829,0.88]
f_measure
0.7530364372469636 [0.789474,0.692308]
f_measure
0.938259109311741 [0.947368,0.923077]
f_measure
0.9684517497348887 [0.97561,0.956522]
f_measure
0.7845345345345345 [0.810811,0.740741]
f_measure
0.844871794871795 [0.871795,0.8]
f_measure
0.844871794871795 [0.871795,0.8]
f_measure
0.8445136852394917 [0.848485,0.83871]
f_measure
0.8043831168831169 [0.857143,0.727273]
kappa
0.8695652173913044
kappa
0.8070175438596491
kappa
0.4838709677419355
kappa
0.8709677419354839
kappa
0.9322033898305084
kappa
0.5555555555555556
kappa
0.6721311475409836
kappa
0.6721311475409836
kappa
0.6946564885496184
kappa
0.5914893617021276
kb_relative_information_score
28.40294819880317
kb_relative_information_score
26.547358986685097
kb_relative_information_score
14.484852432892401
kb_relative_information_score
27.440428455323012
kb_relative_information_score
29.5996911257358
kb_relative_information_score
16.6441151032986
kb_relative_information_score
20.962640444111003
kb_relative_information_score
20.962640444111003
kb_relative_information_score
21.748695567887122
kb_relative_information_score
19.500685375611663
mean_absolute_error
0.0689827887143846
mean_absolute_error
0.09401372910823969
mean_absolute_error
0.25
mean_absolute_error
0.06250000000013725
mean_absolute_error
0.03125
mean_absolute_error
0.21875
mean_absolute_error
0.15625
mean_absolute_error
0.15625
mean_absolute_error
0.15445408792949963
mean_absolute_error
0.18750009649652963
mean_prior_absolute_error
0.4757762813318369
mean_prior_absolute_error
0.4757762813318369
mean_prior_absolute_error
0.47145061728395066
mean_prior_absolute_error
0.47145061728395066
mean_prior_absolute_error
0.47145061728395066
mean_prior_absolute_error
0.47145061728395066
mean_prior_absolute_error
0.47145061728395066
mean_prior_absolute_error
0.47145061728395066
mean_prior_absolute_error
0.478587962962963
mean_prior_absolute_error
0.478587962962963
number_of_instances
33 [20,13]
number_of_instances
33 [20,13]
number_of_instances
32 [20,12]
number_of_instances
32 [20,12]
number_of_instances
32 [20,12]
number_of_instances
32 [20,12]
number_of_instances
32 [20,12]
number_of_instances
32 [20,12]
number_of_instances
32 [19,13]
number_of_instances
32 [19,13]
precision
0.9449035812672175 [0.909091,1]
precision
0.9094516594516594 [0.904762,0.916667]
precision
0.761904761904762 [0.833333,0.642857]
precision
0.9464285714285714 [1,0.857143]
precision
0.9702380952380952 [0.952381,1]
precision
0.8014705882352942 [0.882353,0.666667]
precision
0.8476720647773279 [0.894737,0.769231]
precision
0.8476720647773279 [0.894737,0.769231]
precision
0.8871527777777778 [1,0.722222]
precision
0.8257850241545894 [0.782609,0.888889]
predictive_accuracy
0.9393939393939393
predictive_accuracy
0.9090909090909091
predictive_accuracy
0.75
predictive_accuracy
0.9375
predictive_accuracy
0.96875
predictive_accuracy
0.78125
predictive_accuracy
0.84375
predictive_accuracy
0.84375
predictive_accuracy
0.84375
predictive_accuracy
0.8125
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
prior_entropy
0.9620372403199735
recall
0.9393939393939394 [1,0.846154]
recall
0.9090909090909091 [0.95,0.846154]
recall
0.75 [0.75,0.75]
recall
0.9375 [0.9,1]
recall
0.96875 [1,0.916667]
recall
0.78125 [0.75,0.833333]
recall
0.84375 [0.85,0.833333]
recall
0.84375 [0.85,0.833333]
recall
0.84375 [0.736842,1]
recall
0.8125 [0.947368,0.615385]
relative_absolute_error
0.14498996991039906
relative_absolute_error
0.19760070603996435
relative_absolute_error
0.5302782324058919
relative_absolute_error
0.1325695581017641
relative_absolute_error
0.06628477905073649
relative_absolute_error
0.4639934533551554
relative_absolute_error
0.33142389525368243
relative_absolute_error
0.33142389525368243
relative_absolute_error
0.3227287351175034
relative_absolute_error
0.39177771069649714
root_mean_prior_squared_error
0.48868942835641166
root_mean_prior_squared_error
0.48868942835641166
root_mean_prior_squared_error
0.484243423640869
root_mean_prior_squared_error
0.484243423640869
root_mean_prior_squared_error
0.484243423640869
root_mean_prior_squared_error
0.484243423640869
root_mean_prior_squared_error
0.484243423640869
root_mean_prior_squared_error
0.484243423640869
root_mean_prior_squared_error
0.49155776773278886
root_mean_prior_squared_error
0.49155776773278886
root_mean_squared_error
0.24927722749363973
root_mean_squared_error
0.30203835947535235
root_mean_squared_error
0.5
root_mean_squared_error
0.25
root_mean_squared_error
0.1767766952966369
root_mean_squared_error
0.46770717334674267
root_mean_squared_error
0.39528470752104744
root_mean_squared_error
0.39528470752104744
root_mean_squared_error
0.39084489888472906
root_mean_squared_error
0.4330127018925634
root_relative_squared_error
0.5100933497416206
root_relative_squared_error
0.618057895156818
root_relative_squared_error
1.032538544851394
root_relative_squared_error
0.516269272425697
root_relative_squared_error
0.3650575034504555
root_relative_squared_error
0.9658513683680087
root_relative_squared_error
0.8162933934115825
root_relative_squared_error
0.8162933934115825
root_relative_squared_error
0.7951148868777365
root_relative_squared_error
0.8808989101926865
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