Run
46816

Run 46816

Task 1736 (Learning Curve) diabetes 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
0.6959 ± 0.0615
Per class
Build CPU time
0.0021
Build memory
905391571.8
F measure
0.7274 ± 0.0558
Per class
Kappa
0.3966 ± 0.126
KB relative information score
0.3797 ± 0.1258
Mean absolute error
0.2708 ± 0.0546
Mean prior absolute error
0.4545 ± 0.0015
Number of instances
768
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7261 ± 0.0573
Per class
Predictive accuracy
0.7292 ± 0.0546
Prior entropy
0.9331 ± 0.0046
Recall
0.7292 ± 0.0546
Per class
Relative absolute error
0.5959 ± 0.1206
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.5204 ± 0.0531
Root relative squared error
1.0918 ± 0.112
SciMark benchmark
1495.1153