DEVELOPMENT... OpenML
Run
67676

Run 67676

Task 3756 (Supervised Classification) visualizing_hamster Uploaded 30-11-2014 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_RandomTree(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.RealAdaBoost_RandomTree(1)_P100
weka.RealAdaBoost_RandomTree(1)_H1.0
weka.RealAdaBoost_RandomTree(1)_S1
weka.RealAdaBoost_RandomTree(1)_I10
weka.RealAdaBoost_RandomTree(1)_Wweka.classifiers.trees.RandomTree

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
0.7072
Per class
Build CPU time
0.0072
Build memory
745213491.726
F measure
0.7042
Per class
Kappa
0.4051
KB relative information score
28.6714
Mean absolute error
0.3002
Mean prior absolute error
0.4955
Number of instances
73
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7192
Per class
Predictive accuracy
0.7123
Prior entropy
0.9937
Recall
0.7123
Per class
Relative absolute error
0.6058
Root mean prior squared error
0.4977
Root mean squared error
0.5353
Root relative squared error
1.0755
SciMark benchmark
905.0866