DEVELOPMENT... OpenML
Run
161237

Run 161237

Task 3895 (Supervised Classification) gina_prior Uploaded 15-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.9381
Per class
F measure
0.8725
Per class
Kappa
0.745
KB relative information score
2361.675
Mean absolute error
0.1675
Mean prior absolute error
0.4999
Number of instances
3468
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8725
Per class
Predictive accuracy
0.8725
Prior entropy
0.9998
Recall
0.8725
Per class
Relative absolute error
0.335
Root mean prior squared error
0.4999
Root mean squared error
0.31
Root relative squared error
0.6201
SciMark benchmark
938.4285
UserCPU time millis
95050
UserCPU time millis testing
10
UserCPU time millis training
95040