Repository storing the code of the ActiveCrowdToolkit: Benchmarking active learning algorithms for crowdsourcing research
Click on ActiveCrowdToolkit.exe. The main screen will pop up.
Open the command line, navigate to the folder containing the toolkit files and run CrowdsourcingModels.exe with the following input parameters:
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Parameter 1: Execution mode = run / aggregate
- run = the default mode for running new experiments
- aggregate = the mode for aggregating results files into a single csv files with mean and standard error of the runs
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Parameter 2 (only for run mode): Path to the input dataset in csv format <WorkerID, TaskID, WorkerLabel, GoldLabel (optional)>
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Parameter 3 (only for run mode): Task selection method = RT / ET
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RT = Random task selection
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ET = Entropy task selection
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Parameter 4 (only for run mode): Worker selection method = RW / BT
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RW = Random worker selection
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BT = Entropy worker selection
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Parameter 5 (only for run mode): Index of the starting run
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Parameter 6 (only for run mode): Index of the ending run
This will run all the available aggregation models (Majority vote, Vote distribution, Dawid&Skene, BCC, CBCC) and save the results in a default folder: ResultsActiveLearningToolkit/RunX
Examples:
Execute all the models with ET and RW for 1 to 10 runs:
CrowdsourcingModels.exe Datasets/WS-AMT.csv ET RW 1 10