DEVELOPMENT... OpenML
Run
65047

Run 65047

Task 2098 (Learning Curve) abalone Uploaded 19-11-2014 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_JRip(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1
weka.MultiBoostAB_JRip(2)_C3
weka.MultiBoostAB_JRip(2)_P100
weka.MultiBoostAB_JRip(2)_S1
weka.MultiBoostAB_JRip(2)_I10
weka.MultiBoostAB_JRip(2)_Wweka.classifiers.rules.JRip

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.

19 Evaluation measures

Area under ROC curve
0.5529 ± 0.0153
Per class
Build CPU time
0.3179
Build memory
3343285487.3846
Kappa
0.0314 ± 0.0157
KB relative information score
0.0596 ± 0.0139
Mean absolute error
0.0603 ± 0.0004
Mean prior absolute error
0.0618 ± 0
Number of instances
4177
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Predictive accuracy
0.1839 ± 0.0117
Prior entropy
3.6031 ± 0.0188
Recall
0.1839 ± 0.0117
Per class
Relative absolute error
0.9765 ± 0.0069
Root mean prior squared error
0.1757 ± 0
Root mean squared error
0.1753 ± 0.0009
Root relative squared error
0.9978 ± 0.0054
SciMark benchmark
1605.1864