Run
59580

Run 59580

Task 1730 (Learning Curve) credit-g Uploaded 15-11-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_IBk(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0
weka.MultiBoostAB_IBk(2)_C3
weka.MultiBoostAB_IBk(2)_P100
weka.MultiBoostAB_IBk(2)_S1
weka.MultiBoostAB_IBk(2)_I10
weka.MultiBoostAB_IBk(2)_Wweka.classifiers.lazy.IBk

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
0.6486 ± 0.0459
Per class
Build CPU time
0.0401
Build memory
1025178483.2
F measure
0.7118 ± 0.0381
Per class
Kappa
0.3053 ± 0.0939
KB relative information score
0.274 ± 0.094
Mean absolute error
0.2845 ± 0.0368
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7088 ± 0.0399
Per class
Predictive accuracy
0.716 ± 0.0369
Prior entropy
0.8813
Recall
0.716 ± 0.0369
Per class
Relative absolute error
0.6771 ± 0.0876
Root mean prior squared error
0.4583
Root mean squared error
0.5323 ± 0.0343
Root relative squared error
1.1616 ± 0.0748
SciMark benchmark
947.0414