DEVELOPMENT... OpenML
Run
159246

Run 159246

Task 3612 (Supervised Classification) fri_c1_250_25 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
0.9333
Per class
F measure
0.8474
Per class
Kappa
0.6874
KB relative information score
157.1353
Mean absolute error
0.1904
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
0.8477
Per class
Predictive accuracy
0.848
Prior entropy
0.9852
Recall
0.848
Per class
Relative absolute error
0.3888
Root mean prior squared error
0.4948
Root mean squared error
0.3199
Root relative squared error
0.6465
SciMark benchmark
924.6116
UserCPU time millis
50
UserCPU time millis training
50