DEVELOPMENT... OpenML
Run
163753

Run 163753

Task 3535 (Supervised Classification) tr41.wc Uploaded 16-02-2015 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)_I160
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
0.9694
Per class
F measure
0.924
Per class
Kappa
0.9101
KB relative information score
784.5717
Mean absolute error
0.0152
Mean prior absolute error
0.1652
Number of instances
878
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9276
Per class
Predictive accuracy
0.926
Prior entropy
2.8041
Recall
0.926
Per class
Relative absolute error
0.0918
Root mean prior squared error
0.2872
Root mean squared error
0.1207
Root relative squared error
0.4202
SciMark benchmark
942.6953
UserCPU time millis
10244580
UserCPU time millis training
10244580