Run
439044

Run 439044

Task 1764 (Learning Curve) electricity Uploaded 15-05-2015 by Joaquin Vanschoren
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.SMO_RBFKernel(3)J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998. S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649. Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. In: Advances in Neural Information Processing Systems, 1998.
weka.RBFKernel(3)_G0.01
weka.RBFKernel(3)_C250007
weka.SMO_RBFKernel(3)_C1.0
weka.SMO_RBFKernel(3)_N0
weka.SMO_RBFKernel(3)_L0.001
weka.SMO_RBFKernel(3)_P1.0E-12
weka.SMO_RBFKernel(3)_V-1
weka.SMO_RBFKernel(3)_W1
weka.SMO_RBFKernel(3)_Kweka.classifiers.functions.supportVector.RBFKernel

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.

22 Evaluation measures

Area under ROC curve
0.6626 ± 0.0043
Per class
F measure
0.6776 ± 0.0043
Per class
Kappa
0.3389 ± 0.0088
KB relative information score
0.3593 ± 0.0083
Mean absolute error
0.3099 ± 0.004
Mean prior absolute error
0.4886 ± 0
Number of instances
45312
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6911 ± 0.0045
Per class
Predictive accuracy
0.6901 ± 0.004
Prior entropy
0.9835 ± 0
Recall
0.6901 ± 0.004
Per class
Relative absolute error
0.6343 ± 0.0082
Root mean prior squared error
0.4943 ± 0
Root mean squared error
0.5567 ± 0.0036
Root relative squared error
1.1263 ± 0.0073
SciMark benchmark
938.3666
UserCPU time millis
7248630
UserCPU time millis testing
492580
UserCPU time millis training
6756050