DEVELOPMENT... OpenML
Run
61535

Run 61535

Task 1711 (Learning Curve) mfeat-factors 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
0.9922 ± 0.0043
Per class
Build CPU time
1.9044
Build memory
2596563568.4364
F measure
0.949 ± 0.0144
Per class
Kappa
0.9433 ± 0.0159
KB relative information score
0.9519 ± 0.0134
Mean absolute error
0.0099 ± 0.0027
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9492 ± 0.0123
Per class
Predictive accuracy
0.949 ± 0.0143
Prior entropy
3.3219
Recall
0.949 ± 0.0143
Per class
Relative absolute error
0.0548 ± 0.0152
Root mean prior squared error
0.3
Root mean squared error
0.0935 ± 0.0133
Root relative squared error
0.3115 ± 0.0444
SciMark benchmark
1645.3141