DEVELOPMENT... OpenML
Run
157765

Run 157765

Task 2276 (Supervised Classification) meta_stream_intervals.arff 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
0.9967
Per class
F measure
0.9672
Per class
Kappa
0.9529
KB relative information score
41593.1121
Mean absolute error
0.0142
Mean prior absolute error
0.1072
Number of instances
45164
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9672
Per class
Predictive accuracy
0.9673
Prior entropy
2.3329
Recall
0.9673
Per class
Relative absolute error
0.1328
Root mean prior squared error
0.2315
Root mean squared error
0.0675
Root relative squared error
0.2917
SciMark benchmark
932.3943
UserCPU time millis
403080
UserCPU time millis testing
120
UserCPU time millis training
402960