Run
59869

Run 59869

Task 2098 (Learning Curve) abalone Uploaded 15-11-2014 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.

19 Evaluation measures

Area under ROC curve
0.6999 ± 0.0078
Per class
Build CPU time
6.9487
Build memory
167109541.4154
Kappa
0.1018 ± 0.017
KB relative information score
0.1581 ± 0.004
Mean absolute error
0.0591 ± 0.0001
Mean prior absolute error
0.0618 ± 0
Number of instances
4177
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Predictive accuracy
0.2253 ± 0.0146
Prior entropy
3.6031 ± 0.0188
Recall
0.2253 ± 0.0146
Per class
Relative absolute error
0.9568 ± 0.0024
Root mean prior squared error
0.1757 ± 0
Root mean squared error
0.1718 ± 0.0005
Root relative squared error
0.9778 ± 0.0028
SciMark benchmark
1091.0812