DEVELOPMENT... OpenML
Run
199917

Run 199917

Task 4549 (Supervised Classification) kdd_internet_usage Uploaded 27-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.SMO_PolyKernel(10)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.PolyKernel(8)_E1.0
weka.PolyKernel(8)_C250007
weka.SMO_PolyKernel(10)_C1.0
weka.SMO_PolyKernel(10)_N0
weka.SMO_PolyKernel(10)_L0.001
weka.SMO_PolyKernel(10)_P1.0E-12
weka.SMO_PolyKernel(10)_V-1
weka.SMO_PolyKernel(10)_W1
weka.SMO_PolyKernel(10)_Kweka.classifiers.functions.supportVector.PolyKernel

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
0.8589
Per class
F measure
0.8952
Per class
Kappa
0.731
KB relative information score
71735.4002
Mean absolute error
0.1038
Mean prior absolute error
0.3929
Number of instances
101080
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.8948
Per class
Predictive accuracy
0.8962
Prior entropy
0.8395
Recall
0.8962
Per class
Relative absolute error
0.2641
Root mean prior squared error
0.4432
Root mean squared error
0.3222
Root relative squared error
0.7269
SciMark benchmark
825.5282
UserCPU time millis
707270
UserCPU time millis testing
150
UserCPU time millis training
707120