DEVELOPMENT... OpenML
Run
57901

Run 57901

Task 2094 (Learning Curve) adult Uploaded 13-11-2014 by Jason
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
Issue #Downvotes for this reason By


Flow

weka.AdaBoostM1_REPTree(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_REPTree(2)_I10
weka.AdaBoostM1_REPTree(2)_P100
weka.AdaBoostM1_REPTree(2)_S1
weka.AdaBoostM1_REPTree(2)_Wweka.classifiers.trees.REPTree
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.8769 ± 0.0045
Per class
Build CPU time
0.7583
Build memory
2424645766.76
F measure
0.8285 ± 0.0069
Per class
Kappa
0.5201 ± 0.02
KB relative information score
0.4326 ± 0.0159
Mean absolute error
0.1862 ± 0.005
Mean prior absolute error
0.3641 ± 0
Number of instances
48842
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8264 ± 0.0071
Per class
Predictive accuracy
0.832 ± 0.0064
Prior entropy
0.7938 ± 0.0002
Recall
0.832 ± 0.0064
Per class
Relative absolute error
0.5113 ± 0.0137
Root mean prior squared error
0.4266 ± 0.0001
Root mean squared error
0.3621 ± 0.005
Root relative squared error
0.8488 ± 0.0117
SciMark benchmark
1614.7273