Run
3

Run 3

Task 95 (Learning Curve) segment Uploaded 06-04-2014 by Jan van Rijn
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Flow

weka.HoeffdingTree(1)Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. In: ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 97-106, 2001.
weka.HoeffdingTree(1)_E1.0E-7
weka.HoeffdingTree(1)_G200.0
weka.HoeffdingTree(1)_H0.05
weka.HoeffdingTree(1)_L2
weka.HoeffdingTree(1)_M0.01
weka.HoeffdingTree(1)_N0.0
weka.HoeffdingTree(1)_S1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.9636 ± 0.0073
Per class
F measure
0.7784 ± 0.0228
Per class
Kappa
0.7631 ± 0.024
KB relative information score
0.7847 ± 0.0198
Mean absolute error
0.0587 ± 0.0053
Mean prior absolute error
0.2449
Number of instances
23100
Per class
OS information
[ Oracle Corporation, 1.7.0_51, amd64, Linux, 3.7.10-1.28-desktop ]
Precision
0.8115 ± 0.0301
Per class
Predictive accuracy
0.797 ± 0.0206
Prior entropy
2.8074
Recall
0.797 ± 0.0206
Per class
Relative absolute error
0.2396 ± 0.0217
Root mean prior squared error
0.3499
Root mean squared error
0.2319 ± 0.0107
Root relative squared error
0.6626 ± 0.0305
SciMark benchmark
1970.8627