DEVELOPMENT... OpenML
Run
160013

Run 160013

Task 3638 (Supervised Classification) quake Uploaded 13-02-2015 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)_I80
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
0.5209
Per class
F measure
0.5018
Per class
Kappa
0.0207
KB relative information score
12.2231
Mean absolute error
0.4912
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
0.5193
Per class
Predictive accuracy
0.5404
Prior entropy
0.9912
Recall
0.5404
Per class
Relative absolute error
0.9945
Root mean prior squared error
0.497
Root mean squared error
0.5022
Root relative squared error
1.0105
SciMark benchmark
924.6116
UserCPU time millis
170
UserCPU time millis testing
10
UserCPU time millis training
160