DEVELOPMENT... OpenML
Run
159294

Run 159294

Task 3667 (Supervised Classification) pbcseq 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
0.8143
Per class
F measure
0.7352
Per class
Kappa
0.4704
KB relative information score
667.2909
Mean absolute error
0.3418
Mean prior absolute error
0.5
Number of instances
1945
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7352
Per class
Predictive accuracy
0.7352
Prior entropy
1
Recall
0.7352
Per class
Relative absolute error
0.6837
Root mean prior squared error
0.5
Root mean squared error
0.42
Root relative squared error
0.8399
SciMark benchmark
924.6116
UserCPU time millis
210
UserCPU time millis training
210