DEVELOPMENT... OpenML
Run
122378

Run 122378

Task 1778 (Supervised Classification) mfeat-fourier Uploaded 14-12-2014 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.AdaBoostM1_LWL_DecisionStump(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_LWL_DecisionStump(2)_I160
weka.AdaBoostM1_LWL_DecisionStump(2)_P100
weka.AdaBoostM1_LWL_DecisionStump(2)_S1
weka.AdaBoostM1_LWL_DecisionStump(2)_Wweka.classifiers.lazy.LWL
weka.LWL_DecisionStump(2)_Atrue
weka.LWL_DecisionStump(2)_K-1
weka.LWL_DecisionStump(2)_U0
weka.LWL_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump

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
0.8871
Per class
Build CPU time
320.754
Build memory
454273306.4
F measure
0.5543
Per class
Kappa
0.5348
KB relative information score
3024.1062
Mean absolute error
0.1579
Mean prior absolute error
0.18
Number of instances
10000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6141
Per class
Predictive accuracy
0.5813
Prior entropy
3.3219
Recall
0.5813
Per class
Relative absolute error
0.8773
Root mean prior squared error
0.3
Root mean squared error
0.2731
Root relative squared error
0.9103
SciMark benchmark
919.0358