DEVELOPMENT... OpenML
Run
157005

Run 157005

Task 3667 (Supervised Classification) pbcseq Uploaded 11-02-2015 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)_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
0.7829
Per class
F measure
0.7177
Per class
Kappa
0.4355
KB relative information score
574.7104
Mean absolute error
0.3657
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
0.7178
Per class
Predictive accuracy
0.7177
Prior entropy
1
Recall
0.7177
Per class
Relative absolute error
0.7314
Root mean prior squared error
0.5
Root mean squared error
0.4372
Root relative squared error
0.8744
SciMark benchmark
931.2336
UserCPU time millis
50
UserCPU time millis training
50