Run
64909

Run 64909

Task 1719 (Learning Curve) mfeat-pixel Uploaded 18-11-2014 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
0.9785 ± 0.0108
Per class
Build CPU time
180.2045
Build memory
1057867503.5636
F measure
0.8198 ± 0.0426
Per class
Kappa
0.8044 ± 0.0441
KB relative information score
0.8168 ± 0.0432
Mean absolute error
0.0395 ± 0.0081
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
0.8483 ± 0.0289
Per class
Predictive accuracy
0.824 ± 0.0397
Prior entropy
3.3219
Recall
0.824 ± 0.0397
Per class
Relative absolute error
0.2193 ± 0.0452
Root mean prior squared error
0.3
Root mean squared error
0.1715 ± 0.0215
Root relative squared error
0.5716 ± 0.0716
SciMark benchmark
1605.1864