Run
690

Run 690

Task 99 (Learning Curve) glass Uploaded 07-04-2014 by Jan van Rijn
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Flow

weka.J48(1)Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
weka.J48(1)_C0.25
weka.J48(1)_M2

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
0.8023 ± 0.0735
Per class
F measure
0.667 ± 0.1064
Per class
Kappa
0.5499 ± 0.1356
KB relative information score
0.5883 ± 0.1122
Mean absolute error
0.1014 ± 0.0254
Mean prior absolute error
0.2116 ± 0.0025
Number of instances
2140
Per class
OS information
[ Sun Microsystems Inc., 1.6.0_30, amd64, Linux, 2.6.32-358.6.2.el6.x86_64 ]
Precision
0.6656 ± 0.1109
Per class
Predictive accuracy
0.6701 ± 0.0991
Prior entropy
2.1835 ± 0.0748
Recall
0.6701 ± 0.0991
Per class
Relative absolute error
0.4792 ± 0.1191
Root mean prior squared error
0.3244 ± 0.0039
Root mean squared error
0.2884 ± 0.0432
Root relative squared error
0.8888 ± 0.1317
SciMark benchmark
892.3432