DEVELOPMENT... OpenML
Run
160927

Run 160927

Task 3612 (Supervised Classification) fri_c1_250_25 Uploaded 15-02-2015 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
0.9327
Per class
F measure
0.8439
Per class
Kappa
0.681
KB relative information score
165.6991
Mean absolute error
0.1649
Mean prior absolute error
0.4897
Number of instances
250
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8438
Per class
Predictive accuracy
0.844
Prior entropy
0.9852
Recall
0.844
Per class
Relative absolute error
0.3368
Root mean prior squared error
0.4948
Root mean squared error
0.3485
Root relative squared error
0.7044
SciMark benchmark
936.6206
UserCPU time millis
190
UserCPU time millis training
190