Run
46826

Run 46826

Task 1752 (Learning Curve) vehicle 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
0.8033 ± 0.0237
Per class
Build CPU time
0.0021
Build memory
3149290234.0444
F measure
0.7052 ± 0.0355
Per class
Kappa
0.6075 ± 0.0473
KB relative information score
0.6456 ± 0.0427
Mean absolute error
0.1472 ± 0.0177
Mean prior absolute error
0.3748 ± 0
Number of instances
846
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7052 ± 0.036
Per class
Predictive accuracy
0.7057 ± 0.0354
Prior entropy
1.9991 ± 0.0005
Recall
0.7057 ± 0.0354
Per class
Relative absolute error
0.3926 ± 0.0473
Root mean prior squared error
0.4329 ± 0
Root mean squared error
0.3836 ± 0.0233
Root relative squared error
0.8861 ± 0.0539
SciMark benchmark
1608.9012