DEVELOPMENT... OpenML
Run
61620

Run 61620

Task 1715 (Learning Curve) mfeat-karhunen Uploaded 16-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_RandomForest(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1
weka.MultiBoostAB_RandomForest(2)_C3
weka.MultiBoostAB_RandomForest(2)_P100
weka.MultiBoostAB_RandomForest(2)_S1
weka.MultiBoostAB_RandomForest(2)_I10
weka.MultiBoostAB_RandomForest(2)_Wweka.classifiers.trees.RandomForest

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
0.9975 ± 0.0018
Per class
Build CPU time
0.3363
Build memory
1200092102.7636
F measure
0.9645 ± 0.018
Per class
Kappa
0.9606 ± 0.0199
KB relative information score
0.805 ± 0.0135
Mean absolute error
0.0639 ± 0.0027
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9648 ± 0.0178
Per class
Predictive accuracy
0.9645 ± 0.0179
Prior entropy
3.3219
Recall
0.9645 ± 0.0179
Per class
Relative absolute error
0.3551 ± 0.0149
Root mean prior squared error
0.3
Root mean squared error
0.1325 ± 0.0063
Root relative squared error
0.4415 ± 0.021
SciMark benchmark
1559.5381