119
30957
Python_3.8.18. Sklearn_0.23.1. NumPy_1.23.5. SciPy_1.10.1.
cv
3
30957
error_score
NaN
30957
iid
"deprecated"
30957
n_jobs
null
30957
param_grid
{"base_estimator__C": [0.01, 0.1, 10], "base_estimator__gamma": [0.01, 0.1, 10]}
30957
pre_dispatch
"2*n_jobs"
30957
refit
true
30957
return_train_score
false
30957
scoring
null
30957
verbose
0
30957
bootstrap
true
30958
bootstrap_features
false
30958
max_features
1.0
30958
max_samples
1.0
30958
n_estimators
10
30958
n_jobs
null
30958
oob_score
false
30958
random_state
33003
30958
verbose
0
30958
warm_start
false
30958
C
1.0
30959
break_ties
false
30959
cache_size
200
30959
class_weight
null
30959
coef0
0.0
30959
decision_function_shape
"ovr"
30959
degree
3
30959
gamma
"scale"
30959
kernel
"rbf"
30959
max_iter
-1
30959
probability
false
30959
random_state
62501
30959
shrinking
true
30959
tol
0.001
30959
verbose
false
30959
openml-python
Sklearn_0.23.1.
usercpu_time_millis_training
1385.3194000000003
wall_clock_time_millis_training
1385.3480815887451
usercpu_time_millis_testing
17.93469999999786
usercpu_time_millis
1403.2540999999983
wall_clock_time_millis_testing
17.93694496154785
wall_clock_time_millis
1451.1446952819824
predictive_accuracy
0.6482213438735178