DEVELOPMENT... OpenML
Run
157998

Run 157998

Task 3638 (Supervised Classification) quake 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)_I20
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
0.5348
Per class
F measure
0.5022
Per class
Kappa
0.0439
KB relative information score
16.5352
Mean absolute error
0.4908
Mean prior absolute error
0.4939
Number of instances
2178
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5392
Per class
Predictive accuracy
0.5565
Prior entropy
0.9912
Recall
0.5565
Per class
Relative absolute error
0.9937
Root mean prior squared error
0.497
Root mean squared error
0.4993
Root relative squared error
1.0047
SciMark benchmark
947.9494
UserCPU time millis
40
UserCPU time millis training
40