Run
46789

Run 46789

Task 1702 (Learning Curve) kr-vs-kp Uploaded 04-11-2014 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_RandomTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.MultiBoostAB_RandomTree(2)_C3
weka.MultiBoostAB_RandomTree(2)_P100
weka.MultiBoostAB_RandomTree(2)_S1
weka.MultiBoostAB_RandomTree(2)_I10
weka.MultiBoostAB_RandomTree(2)_Wweka.classifiers.trees.RandomTree

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
0.9622 ± 0.0193
Per class
Build CPU time
0.0046
Build memory
123039762.9333
F measure
0.9621 ± 0.0198
Per class
Kappa
0.9241 ± 0.0396
KB relative information score
0.9243 ± 0.039
Mean absolute error
0.0378 ± 0.0195
Mean prior absolute error
0.499 ± 0.0001
Number of instances
3196
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9621 ± 0.0193
Per class
Predictive accuracy
0.9621 ± 0.0197
Prior entropy
0.9986 ± 0.0002
Recall
0.9621 ± 0.0197
Per class
Relative absolute error
0.0757 ± 0.039
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.194 ± 0.0492
Root relative squared error
0.3884 ± 0.0985
SciMark benchmark
1591.1066