DEVELOPMENT... OpenML
Run
159639

Run 159639

Task 2075 (Supervised Classification) abalone 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)_I80
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
0.7576
Per class
F measure
0.2428
Per class
Kappa
0.1591
KB relative information score
1041.6045
Mean absolute error
0.0553
Mean prior absolute error
0.0618
Number of instances
4177
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.2369
Per class
Predictive accuracy
0.2583
Prior entropy
3.6268
Recall
0.2583
Per class
Relative absolute error
0.8957
Root mean prior squared error
0.1757
Root mean squared error
0.1698
Root relative squared error
0.9663
SciMark benchmark
933.1776
UserCPU time millis
17070
UserCPU time millis testing
20
UserCPU time millis training
17050