DEVELOPMENT... OpenML
Run
123103

Run 123103

Task 3704 (Supervised Classification) kdd_el_nino-small Uploaded 17-12-2014 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.AdaBoostM1_LWL_DecisionStump(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_LWL_DecisionStump(2)_I80
weka.AdaBoostM1_LWL_DecisionStump(2)_P100
weka.AdaBoostM1_LWL_DecisionStump(2)_S1
weka.AdaBoostM1_LWL_DecisionStump(2)_Wweka.classifiers.lazy.LWL
weka.LWL_DecisionStump(2)_Atrue
weka.LWL_DecisionStump(2)_K-1
weka.LWL_DecisionStump(2)_U0
weka.LWL_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump

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.

21 Evaluation measures

Area under ROC curve
0.9748
Per class
Build CPU time
149.2345
Build memory
28584342.5473
F measure
0.9473
Per class
Kappa
0.8838
KB relative information score
688.1059
Mean absolute error
0.0525
Mean prior absolute error
0.4553
Number of instances
782
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9475
Per class
Predictive accuracy
0.9476
Prior entropy
0.9348
Recall
0.9476
Per class
Relative absolute error
0.1154
Root mean prior squared error
0.4771
Root mean squared error
0.2244
Root relative squared error
0.4704
SciMark benchmark
940.5537