DEVELOPMENT... OpenML
Run
159439

Run 159439

Task 3833 (Supervised Classification) analcatdata_authorship 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)_I40
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
0.9997
Per class
F measure
0.9917
Per class
Kappa
0.9823
KB relative information score
821.3058
Mean absolute error
0.0115
Mean prior absolute error
0.4698
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
0.9917
Per class
Predictive accuracy
0.9917
Prior entropy
0.9561
Recall
0.9917
Per class
Relative absolute error
0.0245
Root mean prior squared error
0.4846
Root mean squared error
0.0806
Root relative squared error
0.1663
SciMark benchmark
945.6434
UserCPU time millis
450
UserCPU time millis testing
10
UserCPU time millis training
440