DEVELOPMENT... OpenML
Run
122882

Run 122882

Task 1798 (Supervised Classification) postoperative-patient-data Uploaded 16-12-2014 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
0.3722
Per class
Build CPU time
0.3952
Build memory
530763252
F measure
0.5035
Per class
Kappa
-0.2062
KB relative information score
-78.8988
Mean absolute error
0.3184
Mean prior absolute error
0.2871
Number of instances
450
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.494
Per class
Predictive accuracy
0.5133
Prior entropy
1.0305
Recall
0.5133
Per class
Relative absolute error
1.1092
Root mean prior squared error
0.3755
Root mean squared error
0.5532
Root relative squared error
1.4733
SciMark benchmark
931.6517