593627
2
Joaquin Vanschoren
14
Supervised Classification
4019
weka.FilteredClassifier_MultiSearch_J48(2)
6405
weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.MultiFilter -F \"weka.filters.unsupervised.attribute.ReplaceMissingNumericValuesAndIndicate \" -F \"weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant -A first-last -N ? -R 0 -F yyyy-MM-dd\\\'T\\\'HH:mm:ss\" -F \"weka.filters.unsupervised.attribute.RemoveUseless -M 99.0\"" -W weka.classifiers.meta.MultiSearch -- -E ACC -search "weka.core.setupgenerator.MathParameter -property confidenceFactor -min -4.0 -max -1.0 -step 1.0 -base 10.0 -expression pow(BASE,I)" -search "weka.core.setupgenerator.MathParameter -property minNumObj -min 0.0 -max 6.0 -step 1.0 -base 2.0 -expression pow(BASE,I)" -class-label 1 -algorithm "weka.classifiers.meta.multisearch.RandomSearch -sample-size 100.0 -num-folds 2 -test-set . -num-iterations 200 -num-slots 1 -S 1 -num-slots 1" -log-file /home/rijnjnvan/apps/weka-3-7-13 -S 1 -W weka.classifiers.trees.J48 -- -C 0.25 -M 2
C
0.25
1720
M
2
1720
F
weka.filters.MultiFilter -F "weka.filters.unsupervised.attribute.ReplaceMissingNumericValuesAndIndicate " -F "weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant -A first-last -N ? -R 0 -F yyyy-MM-dd\'T\'HH:mm:ss" -F "weka.filters.unsupervised.attribute.RemoveUseless -M 99.0"
4019
W
weka.classifiers.meta.MultiSearch
4019
E
ACC
4020
class-label
1
4020
search
[weka.core.setupgenerator.MathParameter -property confidenceFactor -min -4.0 -max -1.0 -step 1.0 -base 10.0 -expression pow(BASE,I), weka.core.setupgenerator.MathParameter -property minNumObj -min 0.0 -max 6.0 -step 1.0 -base 2.0 -expression pow(BASE,I)]
4020
algorithm
weka.classifiers.meta.multisearch.RandomSearch -sample-size 100.0 -num-folds 2 -test-set . -num-iterations 200 -num-slots 1 -S 1 -num-slots 1
4020
log-file
/home/rijnjnvan/apps/weka-3-7-13
4020
S
1
4020
W
weka.classifiers.trees.J48
4020
weka
weka_3.7.13
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
2057311
description
https://api.openml.org/data/download/2057311/weka_generated_run1800369852377716451.xml
-1
2057315
model_readable
https://api.openml.org/data/download/2057315/WekaModel_weka.classifiers.meta.FilteredClassifier5614405170731027368.model
-1
2057313
model_serialized
https://api.openml.org/data/download/2057313/WekaSerialized_weka.classifiers.meta.FilteredClassifier7985753835533330281.model
-1
2057312
predictions
https://api.openml.org/data/download/2057312/weka_generated_predictions7808303024432513454.arff
-1
2057314
trace
https://api.openml.org/data/download/2057314/optimization_trace1797288030294799779.arff
area_under_roc_curve
0.920341 [0.988283,0.894879,0.965608,0.910701,0.864665,0.936871,0.8383,0.951289,0.971788,0.881022]
average_cost
0
f_measure
0.775369 [0.977444,0.720988,0.916456,0.794045,0.700252,0.827763,0.444444,0.84689,0.932331,0.593074]
kappa
0.753333
kb_relative_information_score
1546.52134
mean_absolute_error
0.051472
mean_prior_absolute_error
0.18
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
os_information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
precision
0.77918 [0.979899,0.712195,0.928205,0.788177,0.705584,0.851852,0.556391,0.811927,0.934673,0.522901]
predictive_accuracy
0.778
prior_entropy
3.321928
recall
0.778 [0.975,0.73,0.905,0.8,0.695,0.805,0.37,0.885,0.93,0.685]
relative_absolute_error
0.285956
root_mean_prior_squared_error
0.3
root_mean_squared_error
0.19096
root_relative_squared_error
0.636533
scimark_benchmark
896.028697 [550.0601191742942, 1005.4552756626294, 475.31730592400976, 898.676705619265, 1550.6340766572803]
total_cost
0
usercpu_time_millis
490
usercpu_time_millis_testing
30
usercpu_time_millis_training
460
area_under_roc_curve
0.954097 [1,0.932083,0.990972,0.890972,0.937361,0.968194,0.899444,0.962083,0.997222,0.962639]
area_under_roc_curve
0.913333 [0.972639,0.876528,0.954722,0.917917,0.923056,0.986111,0.74875,0.93,0.936806,0.886806]
area_under_roc_curve
0.922903 [0.975,0.835556,0.934028,0.864861,0.885556,0.982639,0.905556,0.919444,1,0.926389]
area_under_roc_curve
0.918 [0.997083,0.8875,0.998194,0.981806,0.884583,0.882778,0.862778,0.908472,0.974861,0.801944]
area_under_roc_curve
0.918444 [0.997222,0.836944,0.91,0.955139,0.834028,0.929028,0.864444,0.950278,0.997083,0.910278]
area_under_roc_curve
0.945931 [1,0.983056,0.999722,0.893333,0.877222,0.961111,0.860417,0.973056,0.994722,0.916667]
area_under_roc_curve
0.886611 [0.975,0.905,0.922222,0.888333,0.755556,0.855556,0.849167,0.912778,0.972222,0.830278]
area_under_roc_curve
0.927972 [0.971667,0.889306,0.997083,0.899167,0.846111,0.959861,0.898889,0.988889,0.93375,0.895]
area_under_roc_curve
0.926736 [1,0.921111,0.994444,0.940556,0.89875,0.918333,0.791944,0.990278,1,0.811944]
area_under_roc_curve
0.891583 [1,0.85875,0.963889,0.865556,0.858333,0.949722,0.682083,0.963333,0.910278,0.863889]
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
0.76971 [1,0.717949,0.9,0.780488,0.666667,0.894737,0.230769,0.871795,0.9,0.734694]
f_measure
0.755139 [0.974359,0.619048,0.894737,0.769231,0.769231,0.837209,0.457143,0.761905,0.923077,0.545455]
f_measure
0.76763 [0.974359,0.682927,0.864865,0.684211,0.780488,0.878049,0.47619,0.871795,0.97561,0.487805]
f_measure
0.771668 [0.95,0.714286,0.95,0.826087,0.731707,0.756757,0.590909,0.810811,0.974359,0.411765]
f_measure
0.759257 [0.952381,0.514286,0.918919,0.809524,0.685714,0.756757,0.611111,0.782609,0.909091,0.652174]
f_measure
0.7829 [1,0.878049,0.952381,0.75,0.6,0.833333,0.424242,0.869565,0.95,0.571429]
f_measure
0.747666 [0.974359,0.8,0.894737,0.8,0.578947,0.714286,0.363636,0.829268,0.95,0.571429]
f_measure
0.773475 [0.95,0.75,0.95,0.761905,0.6,0.842105,0.444444,0.904762,0.864865,0.666667]
f_measure
0.815935 [1,0.780488,0.95,0.923077,0.820513,0.820513,0.4,0.904762,1,0.56]
f_measure
0.784271 [1,0.727273,0.883721,0.833333,0.777778,0.947368,0.296296,0.863636,0.871795,0.641509]
kappa
0.761111
kappa
0.727778
kappa
0.738889
kappa
0.75
kappa
0.738889
kappa
0.766667
kappa
0.722222
kappa
0.755556
kappa
0.8
kappa
0.772222
kb_relative_information_score
155.359726
kb_relative_information_score
148.398634
kb_relative_information_score
151.639734
kb_relative_information_score
156.159855
kb_relative_information_score
151.036384
kb_relative_information_score
156.332477
kb_relative_information_score
151.746507
kb_relative_information_score
155.392744
kb_relative_information_score
163.171728
kb_relative_information_score
157.28355
mean_absolute_error
0.05408
mean_absolute_error
0.055895
mean_absolute_error
0.057819
mean_absolute_error
0.049087
mean_absolute_error
0.053659
mean_absolute_error
0.052929
mean_absolute_error
0.050552
mean_absolute_error
0.053659
mean_absolute_error
0.042566
mean_absolute_error
0.044472
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
mean_prior_absolute_error
0.18
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
precision
0.783005 [1,0.736842,0.9,0.761905,0.571429,0.944444,0.5,0.894737,0.9,0.62069]
precision
0.760488 [1,0.590909,0.944444,0.789474,0.789474,0.782609,0.533333,0.727273,0.947368,0.5]
precision
0.772697 [1,0.666667,0.941176,0.722222,0.761905,0.857143,0.454545,0.894737,0.952381,0.47619]
precision
0.777442 [0.95,0.681818,0.95,0.730769,0.714286,0.823529,0.541667,0.882353,1,0.5]
precision
0.769541 [0.909091,0.6,1,0.772727,0.8,0.823529,0.6875,0.692308,0.833333,0.576923]
precision
0.785688 [1,0.857143,0.909091,0.75,0.6,0.9375,0.538462,0.769231,0.95,0.545455]
precision
0.754119 [1,0.8,0.944444,0.8,0.611111,0.681818,0.461538,0.809524,0.95,0.482759]
precision
0.805753 [0.95,0.75,0.95,0.727273,0.6,0.888889,0.857143,0.863636,0.941176,0.529412]
precision
0.827379 [1,0.761905,0.95,0.947368,0.842105,0.842105,0.6,0.863636,1,0.466667]
precision
0.807824 [1,0.666667,0.826087,0.9375,0.875,1,0.571429,0.791667,0.894737,0.515152]
predictive_accuracy
0.785
predictive_accuracy
0.755
predictive_accuracy
0.765
predictive_accuracy
0.775
predictive_accuracy
0.765
predictive_accuracy
0.79
predictive_accuracy
0.75
predictive_accuracy
0.78
predictive_accuracy
0.82
predictive_accuracy
0.795
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
prior_entropy
3.321928
recall
0.785 [1,0.7,0.9,0.8,0.8,0.85,0.15,0.85,0.9,0.9]
recall
0.755 [0.95,0.65,0.85,0.75,0.75,0.9,0.4,0.8,0.9,0.6]
recall
0.765 [0.95,0.7,0.8,0.65,0.8,0.9,0.5,0.85,1,0.5]
recall
0.775 [0.95,0.75,0.95,0.95,0.75,0.7,0.65,0.75,0.95,0.35]
recall
0.765 [1,0.45,0.85,0.85,0.6,0.7,0.55,0.9,1,0.75]
recall
0.79 [1,0.9,1,0.75,0.6,0.75,0.35,1,0.95,0.6]
recall
0.75 [0.95,0.8,0.85,0.8,0.55,0.75,0.3,0.85,0.95,0.7]
recall
0.78 [0.95,0.75,0.95,0.8,0.6,0.8,0.3,0.95,0.8,0.9]
recall
0.82 [1,0.8,0.95,0.9,0.8,0.8,0.3,0.95,1,0.7]
recall
0.795 [1,0.8,0.95,0.75,0.7,0.9,0.2,0.95,0.85,0.85]
relative_absolute_error
0.300447
relative_absolute_error
0.31053
relative_absolute_error
0.321215
relative_absolute_error
0.272708
relative_absolute_error
0.298108
relative_absolute_error
0.294051
relative_absolute_error
0.280844
relative_absolute_error
0.298107
relative_absolute_error
0.236478
relative_absolute_error
0.247068
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_prior_squared_error
0.3
root_mean_squared_error
0.178281
root_mean_squared_error
0.204674
root_mean_squared_error
0.189736
root_mean_squared_error
0.193873
root_mean_squared_error
0.195618
root_mean_squared_error
0.178004
root_mean_squared_error
0.211307
root_mean_squared_error
0.1858
root_mean_squared_error
0.173815
root_mean_squared_error
0.195086
root_relative_squared_error
0.594271
root_relative_squared_error
0.682247
root_relative_squared_error
0.632454
root_relative_squared_error
0.646244
root_relative_squared_error
0.65206
root_relative_squared_error
0.593348
root_relative_squared_error
0.704356
root_relative_squared_error
0.619332
root_relative_squared_error
0.579385
root_relative_squared_error
0.650288
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
930
usercpu_time_millis
810
usercpu_time_millis
460
usercpu_time_millis
550
usercpu_time_millis
590
usercpu_time_millis
590
usercpu_time_millis
610
usercpu_time_millis
580
usercpu_time_millis
620
usercpu_time_millis
630
usercpu_time_millis_testing
20
usercpu_time_millis_testing
10
usercpu_time_millis_testing
10
usercpu_time_millis_testing
10
usercpu_time_millis_testing
10
usercpu_time_millis_testing
10
usercpu_time_millis_testing
10
usercpu_time_millis_testing
10
usercpu_time_millis_testing
0
usercpu_time_millis_testing
0
usercpu_time_millis_training
910
usercpu_time_millis_training
800
usercpu_time_millis_training
450
usercpu_time_millis_training
540
usercpu_time_millis_training
580
usercpu_time_millis_training
580
usercpu_time_millis_training
600
usercpu_time_millis_training
570
usercpu_time_millis_training
620
usercpu_time_millis_training
630