DEVELOPMENT... OpenML
Run
124297

Run 124297

Task 3783 (Supervised Classification) fri_c2_500_50 Uploaded 23-12-2014 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)_I20
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
0.9264
Per class
Build CPU time
149.7622
Build memory
1286893085.6
F measure
0.8681
Per class
Kappa
0.7276
KB relative information score
354.7395
Mean absolute error
0.1398
Mean prior absolute error
0.4839
Number of instances
500
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8682
Per class
Predictive accuracy
0.868
Prior entropy
0.9767
Recall
0.868
Per class
Relative absolute error
0.2889
Root mean prior squared error
0.4918
Root mean squared error
0.3418
Root relative squared error
0.6949
SciMark benchmark
893.4088