DEVELOPMENT... OpenML
Run
161395

Run 161395

Task 4001 (Supervised Classification) pc1_req Uploaded 16-02-2015 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)_I160
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
0.605
Per class
F measure
0.6454
Per class
Kappa
0.1811
KB relative information score
23.5716
Mean absolute error
0.4051
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
0.6541
Per class
Predictive accuracy
0.6813
Prior entropy
0.9204
Recall
0.6813
Per class
Relative absolute error
0.9093
Root mean prior squared error
0.4718
Root mean squared error
0.479
Root relative squared error
1.0152
SciMark benchmark
943.2817
UserCPU time millis
60
UserCPU time millis training
60