Run
1011

Run 1011

Task 94 (Learning Curve) dermatology Uploaded 08-04-2014 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
0.9771 ± 0.0201
Per class
F measure
0.9387 ± 0.0356
Per class
Kappa
0.9234 ± 0.0457
KB relative information score
0.9216 ± 0.0416
Mean absolute error
0.025 ± 0.0114
Mean prior absolute error
0.2664 ± 0.0004
Number of instances
3660
Per class
OS information
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
Precision
0.9388 ± 0.0301
Per class
Predictive accuracy
0.9388 ± 0.0364
Prior entropy
2.4327 ± 0.0089
Recall
0.9388 ± 0.0364
Per class
Relative absolute error
0.0937 ± 0.0429
Root mean prior squared error
0.3649 ± 0.0006
Root mean squared error
0.1345 ± 0.0463
Root relative squared error
0.3685 ± 0.127
SciMark benchmark
880.5119