Run
54806

Run 54806

Task 1713 (Learning Curve) mfeat-fourier Uploaded 10-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.AdaBoostM1_LWL_DecisionStump(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_LWL_DecisionStump(2)_I10
weka.AdaBoostM1_LWL_DecisionStump(2)_P100
weka.AdaBoostM1_LWL_DecisionStump(2)_S1
weka.AdaBoostM1_LWL_DecisionStump(2)_Wweka.classifiers.lazy.LWL
weka.LWL_DecisionStump(2)_Atrue
weka.LWL_DecisionStump(2)_K-1
weka.LWL_DecisionStump(2)_U0
weka.LWL_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump

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
0.8975 ± 0.0121
Per class
Build CPU time
289.2645
Build memory
140038059.2
F measure
0.5927 ± 0.1039
Per class
Kappa
0.5661 ± 0.1007
KB relative information score
0.3155 ± 0.0585
Mean absolute error
0.1556 ± 0.0091
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.6328 ± 0.0757
Per class
Predictive accuracy
0.6095 ± 0.0906
Prior entropy
3.3219
Recall
0.6095 ± 0.0906
Per class
Relative absolute error
0.8646 ± 0.0506
Root mean prior squared error
0.3
Root mean squared error
0.2683 ± 0.0143
Root relative squared error
0.8943 ± 0.0478
SciMark benchmark
1614.7273