DEVELOPMENT... OpenML
Run
160953

Run 160953

Task 3638 (Supervised Classification) quake Uploaded 15-02-2015 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)_I160
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
0.5113
Per class
F measure
0.5014
Per class
Kappa
0.0086
KB relative information score
5.5859
Mean absolute error
0.4923
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
0.5111
Per class
Predictive accuracy
0.5312
Prior entropy
0.9912
Recall
0.5312
Per class
Relative absolute error
0.9966
Root mean prior squared error
0.497
Root mean squared error
0.5053
Root relative squared error
1.0168
SciMark benchmark
936.6206
UserCPU time millis
310
UserCPU time millis training
310