Run
435887

Run 435887

Task 75 (Learning Curve) mfeat-karhunen 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)_I160
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
0.9967 ± 0.0015
Per class
F measure
0.9415 ± 0.0156
Per class
Kappa
0.9351 ± 0.0172
KB relative information score
0.7703 ± 0.0119
Mean absolute error
0.0734 ± 0.0026
Mean prior absolute error
0.18
Number of instances
20000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.942 ± 0.0145
Per class
Predictive accuracy
0.9416 ± 0.0155
Prior entropy
3.3219
Recall
0.9416 ± 0.0155
Per class
Relative absolute error
0.4078 ± 0.0147
Root mean prior squared error
0.3
Root mean squared error
0.1453 ± 0.0049
Root relative squared error
0.4842 ± 0.0165
SciMark benchmark
912.4377
UserCPU time millis
11790
UserCPU time millis testing
250
UserCPU time millis training
11540