DEVELOPMENT... OpenML
Run
159440

Run 159440

Task 3835 (Supervised Classification) squash-stored 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
0.7961
Per class
F measure
0.7308
Per class
Kappa
0.4543
KB relative information score
22.5122
Mean absolute error
0.277
Mean prior absolute error
0.4936
Number of instances
52
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7308
Per class
Predictive accuracy
0.7308
Prior entropy
0.9911
Recall
0.7308
Per class
Relative absolute error
0.5612
Root mean prior squared error
0.4967
Root mean squared error
0.4925
Root relative squared error
0.9917
SciMark benchmark
945.6434
UserCPU time millis
10
UserCPU time millis training
10

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