DEVELOPMENT... OpenML
Run
159576

Run 159576

Task 4001 (Supervised Classification) pc1_req 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
0.6081
Per class
F measure
0.6243
Per class
Kappa
0.1375
KB relative information score
20.917
Mean absolute error
0.4089
Mean prior absolute error
0.4455
Number of instances
320
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6423
Per class
Predictive accuracy
0.675
Prior entropy
0.9204
Recall
0.675
Per class
Relative absolute error
0.9179
Root mean prior squared error
0.4718
Root mean squared error
0.4723
Root relative squared error
1.0011
SciMark benchmark
924.6116
UserCPU time millis
20
UserCPU time millis training
20