DEVELOPMENT... OpenML
Run
156882

Run 156882

Task 3549 (Supervised Classification) analcatdata_authorship Uploaded 11-02-2015 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)_I10
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
0.9998
Per class
F measure
0.994
Per class
Kappa
0.9913
KB relative information score
819.2742
Mean absolute error
0.0121
Mean prior absolute error
0.3439
Number of instances
841
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9941
Per class
Predictive accuracy
0.9941
Prior entropy
1.7898
Recall
0.9941
Per class
Relative absolute error
0.0353
Root mean prior squared error
0.4146
Root mean squared error
0.0573
Root relative squared error
0.1383
SciMark benchmark
902.4773
UserCPU time millis
390
UserCPU time millis training
390