DEVELOPMENT... OpenML
Run
61555

Run 61555

Task 1735 (Learning Curve) segment Uploaded 16-11-2014 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.MultiBoostAB_J48(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.J48(3)_C0.25
weka.J48(3)_M2
weka.MultiBoostAB_J48(2)_C3
weka.MultiBoostAB_J48(2)_P100
weka.MultiBoostAB_J48(2)_S1
weka.MultiBoostAB_J48(2)_I10
weka.MultiBoostAB_J48(2)_Wweka.classifiers.trees.J48

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
0.9951 ± 0.0032
Per class
Build CPU time
0.1685
Build memory
2047086767.1333
F measure
0.9809 ± 0.0074
Per class
Kappa
0.9778 ± 0.0086
KB relative information score
0.9809 ± 0.0084
Mean absolute error
0.0053 ± 0.0022
Mean prior absolute error
0.2449
Number of instances
2310
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.981 ± 0.0074
Per class
Predictive accuracy
0.981 ± 0.0074
Prior entropy
2.8074
Recall
0.981 ± 0.0074
Per class
Relative absolute error
0.0217 ± 0.0092
Root mean prior squared error
0.3499
Root mean squared error
0.0698 ± 0.0162
Root relative squared error
0.1996 ± 0.0463
SciMark benchmark
1591.1714