Run
435062

Run 435062

Task 96 (Learning Curve) diabetes Uploaded 12-05-2015 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.RandomSubSpace_REPTree(4)Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html.
weka.REPTree(9)_M2
weka.REPTree(9)_V0.001
weka.REPTree(9)_N3
weka.REPTree(9)_S1
weka.REPTree(9)_L-1
weka.REPTree(9)_I0.0
weka.RandomSubSpace_REPTree(4)_P0.5
weka.RandomSubSpace_REPTree(4)_S1
weka.RandomSubSpace_REPTree(4)_num-slots1
weka.RandomSubSpace_REPTree(4)_I40
weka.RandomSubSpace_REPTree(4)_Wweka.classifiers.trees.REPTree

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.

22 Evaluation measures

Area under ROC curve
0.8246 ± 0.0466
Per class
F measure
0.7372 ± 0.0465
Per class
Kappa
0.4079 ± 0.1046
KB relative information score
0.2155 ± 0.0437
Mean absolute error
0.3674 ± 0.0158
Mean prior absolute error
0.4545 ± 0.0015
Number of instances
7680
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7516 ± 0.0494
Per class
Predictive accuracy
0.7544 ± 0.0408
Prior entropy
0.9331 ± 0.0044
Recall
0.7544 ± 0.0408
Per class
Relative absolute error
0.8084 ± 0.035
Root mean prior squared error
0.4766 ± 0.0015
Root mean squared error
0.4107 ± 0.0169
Root relative squared error
0.8617 ± 0.0357
SciMark benchmark
913.9348
UserCPU time millis
110
UserCPU time millis testing
20
UserCPU time millis training
90