Run
58878

Run 58878

Task 1731 (Learning Curve) pendigits Uploaded 15-11-2014 by Joaquin Vanschoren
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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
0.9895 ± 0.004
Per class
Build CPU time
938.053
Build memory
801387855.8
F measure
0.8821 ± 0.0236
Per class
Kappa
0.8701 ± 0.0251
KB relative information score
0.7758 ± 0.034
Mean absolute error
0.0667 ± 0.0086
Mean prior absolute error
0.18 ± 0
Number of instances
10992
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8841 ± 0.0239
Per class
Predictive accuracy
0.8831 ± 0.0226
Prior entropy
3.3208 ± 0.0002
Recall
0.8831 ± 0.0226
Per class
Relative absolute error
0.3708 ± 0.0478
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.1481 ± 0.0118
Root relative squared error
0.4936 ± 0.0394
SciMark benchmark
947.0414