DEVELOPMENT... OpenML
Run
11931

Run 11931

Task 34 (Supervised Classification) postoperative-patient-data Uploaded 22-05-2014 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(1)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(1)_F0
weka.LogitBoost_DecisionStump(1)_H1.0
weka.LogitBoost_DecisionStump(1)_I20
weka.LogitBoost_DecisionStump(1)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(1)_P100
weka.LogitBoost_DecisionStump(1)_R1
weka.LogitBoost_DecisionStump(1)_S1
weka.LogitBoost_DecisionStump(1)_Wweka.classifiers.trees.DecisionStump

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.3522
Per class
F measure
0.5854
Per class
Kappa
-0.0377
KB relative information score
-9.125
Mean absolute error
0.3047
Mean prior absolute error
0.2871
Number of instances
90
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5528
Per class
Predictive accuracy
0.6667
Prior entropy
1.0305
Recall
0.6667
Per class
Relative absolute error
1.0616
Root mean prior squared error
0.3755
Root mean squared error
0.4329
Root relative squared error
1.1528
SciMark benchmark
915.3446[563.7494238588241859.4804301482366483.88543266528814909.59057174132591760.017229859821]