DEVELOPMENT... OpenML
Run
156927

Run 156927

Task 3590 (Supervised Classification) analcatdata_vineyard Uploaded 11-02-2015 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)_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
0.8748
Per class
F measure
0.7897
Per class
Kappa
0.5731
KB relative information score
191.7801
Mean absolute error
0.3062
Mean prior absolute error
0.4939
Number of instances
468
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7902
Per class
Predictive accuracy
0.7906
Prior entropy
0.9912
Recall
0.7906
Per class
Relative absolute error
0.62
Root mean prior squared error
0.4969
Root mean squared error
0.3783
Root relative squared error
0.7614
SciMark benchmark
929.566
UserCPU time millis
10
UserCPU time millis training
10