DEVELOPMENT... OpenML
Run
159224

Run 159224

Task 3583 (Supervised Classification) rmftsa_ladata 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
0.9477
Per class
F measure
0.8819
Per class
Kappa
0.76
KB relative information score
355.9354
Mean absolute error
0.1536
Mean prior absolute error
0.4921
Number of instances
508
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8819
Per class
Predictive accuracy
0.8819
Prior entropy
0.9886
Recall
0.8819
Per class
Relative absolute error
0.3121
Root mean prior squared error
0.496
Root mean squared error
0.3007
Root relative squared error
0.6063
SciMark benchmark
924.6116
UserCPU time millis
70
UserCPU time millis training
70