DEVELOPMENT... OpenML
Run
158982

Run 158982

Task 202 (Supervised Classification) BNG(glass,nominal,137781) Uploaded 12-02-2015 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)_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
0.8639
Per class
F measure
0.6386
Per class
Kappa
0.5286
KB relative information score
65626.929
Mean absolute error
0.1367
Mean prior absolute error
0.2115
Number of instances
137781
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6413
Per class
Predictive accuracy
0.6608
Prior entropy
2.2061
Recall
0.6608
Per class
Relative absolute error
0.646
Root mean prior squared error
0.3252
Root mean squared error
0.2597
Root relative squared error
0.7985
SciMark benchmark
931.2336
UserCPU time millis
22310
UserCPU time millis testing
180
UserCPU time millis training
22130