DEVELOPMENT... OpenML
Run
158822

Run 158822

Task 58 (Supervised Classification) waveform-5000 Uploaded 12-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(2)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(2)_E1
weka.LogitBoost_DecisionStump(2)_H1.0
weka.LogitBoost_DecisionStump(2)_I40
weka.LogitBoost_DecisionStump(2)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(2)_O1
weka.LogitBoost_DecisionStump(2)_P100
weka.LogitBoost_DecisionStump(2)_S1
weka.LogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.LogitBoost_DecisionStump(2)_Z3.0

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
0.9645
Per class
F measure
0.848
Per class
Kappa
0.7723
KB relative information score
3749.1259
Mean absolute error
0.1318
Mean prior absolute error
0.4444
Number of instances
5000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8481
Per class
Predictive accuracy
0.8482
Prior entropy
1.5849
Recall
0.8482
Per class
Relative absolute error
0.2966
Root mean prior squared error
0.4714
Root mean squared error
0.2666
Root relative squared error
0.5655
SciMark benchmark
910.8389
UserCPU time millis
6110
UserCPU time millis testing
10
UserCPU time millis training
6100