DEVELOPMENT... OpenML
Run
157541

Run 157541

Task 2264 (Supervised Classification) BNG(hepatitis) 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
0.948
Per class
F measure
0.9043
Per class
Kappa
0.7022
KB relative information score
565271.5027
Mean absolute error
0.1374
Mean prior absolute error
0.3293
Number of instances
1000000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9038
Per class
Predictive accuracy
0.9068
Prior entropy
0.7373
Recall
0.9068
Per class
Relative absolute error
0.4172
Root mean prior squared error
0.4057
Root mean squared error
0.261
Root relative squared error
0.6432
SciMark benchmark
923.9763
UserCPU time millis
185800
UserCPU time millis testing
780
UserCPU time millis training
185020