Run
51792

Run 51792

Task 2098 (Learning Curve) abalone Uploaded 07-11-2014 by Jan van Rijn
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_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I10
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

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
0.7136 ± 0.0157
Per class
Build CPU time
0.0122
Build memory
261093543.8154
Kappa
0.1626 ± 0.0328
KB relative information score
0.2535 ± 0.0114
Mean absolute error
0.0556 ± 0.0005
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
0.2626 ± 0.0275
Prior entropy
3.6031 ± 0.0188
Recall
0.2626 ± 0.0275
Per class
Relative absolute error
0.8993 ± 0.009
Root mean prior squared error
0.1757 ± 0
Root mean squared error
0.1736 ± 0.0028
Root relative squared error
0.9882 ± 0.0157
SciMark benchmark
1609.6362