DEVELOPMENT... OpenML
Run
159194

Run 159194

Task 3549 (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
1
Per class
F measure
0.9952
Per class
Kappa
0.9931
KB relative information score
831.2291
Mean absolute error
0.0042
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
0.9953
Per class
Predictive accuracy
0.9952
Prior entropy
1.7898
Recall
0.9952
Per class
Relative absolute error
0.0121
Root mean prior squared error
0.4146
Root mean squared error
0.0465
Root relative squared error
0.1122
SciMark benchmark
924.6116
UserCPU time millis
1690
UserCPU time millis testing
10
UserCPU time millis training
1680

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