DEVELOPMENT... OpenML
Run
159354

Run 159354

Task 3737 (Supervised Classification) fri_c3_250_50 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
0.9013
Per class
F measure
0.8272
Per class
Kappa
0.6468
KB relative information score
144.0348
Mean absolute error
0.2158
Mean prior absolute error
0.4908
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
0.8277
Per class
Predictive accuracy
0.828
Prior entropy
0.9868
Recall
0.828
Per class
Relative absolute error
0.4396
Root mean prior squared error
0.4954
Root mean squared error
0.3579
Root relative squared error
0.7226
SciMark benchmark
945.6434
UserCPU time millis
110
UserCPU time millis training
110