DEVELOPMENT... OpenML
Run
157252

Run 157252

Task 3913 (Supervised Classification) kc2 Uploaded 11-02-2015 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)_I10
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
0.8183
Per class
F measure
0.8425
Per class
Kappa
0.4961
KB relative information score
166.9769
Mean absolute error
0.2114
Mean prior absolute error
0.3266
Number of instances
522
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8405
Per class
Predictive accuracy
0.8506
Prior entropy
0.734
Recall
0.8506
Per class
Relative absolute error
0.6474
Root mean prior squared error
0.4037
Root mean squared error
0.3386
Root relative squared error
0.8387
SciMark benchmark
931.2336
UserCPU time millis
20
UserCPU time millis training
20