Run
53726

Run 53726

Task 1727 (Learning Curve) optdigits Uploaded 08-11-2014 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
0.9753 ± 0.017
Per class
Build CPU time
402.7803
Build memory
324460654.6286
F measure
0.8024 ± 0.1017
Per class
Kappa
0.7861 ± 0.1021
KB relative information score
0.6065 ± 0.1899
Mean absolute error
0.1028 ± 0.0432
Mean prior absolute error
0.18 ± 0
Number of instances
5620
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8273 ± 0.0646
Per class
Predictive accuracy
0.8075 ± 0.0919
Prior entropy
3.3218 ± 0.0001
Recall
0.8075 ± 0.0919
Per class
Relative absolute error
0.5712 ± 0.24
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.1985 ± 0.0543
Root relative squared error
0.6618 ± 0.1811
SciMark benchmark
1615.5755