DEVELOPMENT... OpenML
Run
52220

Run 52220

Task 1730 (Learning Curve) credit-g Uploaded 07-11-2014 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.RealAdaBoost_RandomForest(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1
weka.RealAdaBoost_RandomForest(1)_P100
weka.RealAdaBoost_RandomForest(1)_H1.0
weka.RealAdaBoost_RandomForest(1)_S1
weka.RealAdaBoost_RandomForest(1)_I10
weka.RealAdaBoost_RandomForest(1)_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
0.7726 ± 0.0369
Per class
Build CPU time
0.9146
Build memory
1030691934.7556
F measure
0.7389 ± 0.0391
Per class
Kappa
0.3552 ± 0.0984
KB relative information score
0.3738 ± 0.0668
Mean absolute error
0.2468 ± 0.0246
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7414 ± 0.0424
Per class
Predictive accuracy
0.756 ± 0.0347
Prior entropy
0.8813
Recall
0.756 ± 0.0347
Per class
Relative absolute error
0.5874 ± 0.0585
Root mean prior squared error
0.4583
Root mean squared error
0.4635 ± 0.0322
Root relative squared error
1.0114 ± 0.0703
SciMark benchmark
946.7958