DEVELOPMENT... OpenML
Run
160292

Run 160292

Task 3536 (Supervised Classification) oh10.wc Uploaded 13-02-2015 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)_I80
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
0.9732
Per class
F measure
0.8196
Per class
Kappa
0.7958
KB relative information score
849.1769
Mean absolute error
0.0395
Mean prior absolute error
0.1768
Number of instances
1050
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8212
Per class
Predictive accuracy
0.82
Prior entropy
3.2054
Recall
0.82
Per class
Relative absolute error
0.2236
Root mean prior squared error
0.2973
Root mean squared error
0.1646
Root relative squared error
0.5539
SciMark benchmark
938.4285
UserCPU time millis
1564490
UserCPU time millis training
1564490