Run
52739

Run 52739

Task 1715 (Learning Curve) mfeat-karhunen Uploaded 07-11-2014 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.MultiBoostAB_LWL_DecisionStump(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.LWL_DecisionStump(2)_Atrue
weka.LWL_DecisionStump(2)_K-1
weka.LWL_DecisionStump(2)_U0
weka.LWL_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.MultiBoostAB_LWL_DecisionStump(2)_C3
weka.MultiBoostAB_LWL_DecisionStump(2)_P100
weka.MultiBoostAB_LWL_DecisionStump(2)_S1
weka.MultiBoostAB_LWL_DecisionStump(2)_I10
weka.MultiBoostAB_LWL_DecisionStump(2)_Wweka.classifiers.lazy.LWL

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
0.9423 ± 0.0151
Per class
Build CPU time
408.4837
Build memory
90943034.2545
F measure
0.747 ± 0.0471
Per class
Kappa
0.7139 ± 0.0478
KB relative information score
0.6829 ± 0.1125
Mean absolute error
0.0776 ± 0.0262
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
0.776 ± 0.0535
Per class
Predictive accuracy
0.7425 ± 0.043
Prior entropy
3.3219
Recall
0.7425 ± 0.043
Per class
Relative absolute error
0.4314 ± 0.1458
Root mean prior squared error
0.3
Root mean squared error
0.1963 ± 0.0212
Root relative squared error
0.6543 ± 0.0707
SciMark benchmark
1615.5755