Run
9190007

Run 9190007

Task 167211 (Supervised Classification) Satellite Uploaded 18-04-2018 by Nikolay Stoyanov
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Evaluation Engine Exception: Illegal combination of evaluation measure attributes (repeat, fold, sample): Measure(s): predictive_accuracy(0, 0, 0), usercpu_time_millis_testing(0, 0, 0), usercpu_time_millis(0, 0, 0), root_mean_squared_error(0, 0, 0), root_relative_squared_error(0, 0, 0), kappa(0, 0, 0), usercpu_time_millis_training(0, 0, 0), predictive_accuracy(0, 1, 0), usercpu_time_millis_testing(0, 1, 0), usercpu_time_millis(0, 1, 0), root_mean_squared_error(0, 1, 0), root_relative_squared_error(0, 1, 0), kappa(0, 1, 0), usercpu_time_millis_training(0, 1, 0), predictive_accuracy(0, 2, 0), usercpu_time_millis_testing(0, 2, 0), usercpu_time_millis(0, 2, 0), root_mean_squared_error(0, 2, 0), root_relative_squared_error(0, 2, 0), kappa(0, 2, 0), usercpu_time_millis_training(0, 2, 0), predictive_accuracy(0, 3, 0), usercpu_time_millis_testing(0, 3, 0), usercpu_time_millis(0, 3, 0), root_mean_squared_error(0, 3, 0), root_relative_squared_error(0, 3, 0), kappa(0, 3, 0), usercpu_time_millis_training(... (message cut-off due to excessive length)
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Flow

weka.IterativeClassifierOptimizer(1)Weka implementation of IterativeClassifierOptimizer
weka.IterativeClassifierOptimizer(1)_L50
weka.IterativeClassifierOptimizer(1)_P1
weka.IterativeClassifierOptimizer(1)_E1
weka.IterativeClassifierOptimizer(1)_I1
weka.IterativeClassifierOptimizer(1)_F10
weka.IterativeClassifierOptimizer(1)_R1
weka.IterativeClassifierOptimizer(1)_percentage0.0
weka.IterativeClassifierOptimizer(1)_Wweka.classifiers.meta.LogitBoost
weka.IterativeClassifierOptimizer(1)_metricRMSE
weka.IterativeClassifierOptimizer(1)_S1

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.

0 Evaluation measures