OpenML
38208

Run 38208

Task 3043 (Supervised Classification) sick Uploaded 28-10-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_ADTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.ADTree(2)_B10
weka.ADTree(2)_E-3
weka.ADTree(2)_S1
weka.MultiBoostAB_ADTree(2)_C3
weka.MultiBoostAB_ADTree(2)_P100
weka.MultiBoostAB_ADTree(2)_S1
weka.MultiBoostAB_ADTree(2)_I20
weka.MultiBoostAB_ADTree(2)_Wweka.classifiers.trees.ADTree

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
0.9502
Per class
Cross-validation details (33% Holdout set)
Build CPU time
2.082
Cross-validation details (33% Holdout set)
Build memory
1025423160
Cross-validation details (33% Holdout set)
F measure
0.984
Per class
Cross-validation details (33% Holdout set)
Kappa
0.8644
Cross-validation details (33% Holdout set)
KB relative information score
1064.3613
Cross-validation details (33% Holdout set)
Mean absolute error
0.016
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.1193
Cross-validation details (33% Holdout set)
Number of instances
1244
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9845
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.9847
Cross-validation details (33% Holdout set)
Prior entropy
0.3333
Cross-validation details (33% Holdout set)
Recall
0.9847
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.1338
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.2482
Cross-validation details (33% Holdout set)
Root mean squared error
0.123
Cross-validation details (33% Holdout set)
Root relative squared error
0.4956
Cross-validation details (33% Holdout set)
SciMark benchmark
942.4851