Skip to main content

Advertisement

Table 11 Comparison on a Full-Retrain with Batch Update on Online-Updating Approach on ActivePMFv2 model learning (Feature k = 20; No of Work Done = 11,000)

From: An online-updating algorithm on probabilistic matrix factorization with active learning for task recommendation in crowdsourcing systems

ActivePMFv2 model MAE RMSE Avg Runtime per Work Done (min)
Full Retrain 0.0156 0.0845 3.839
Online-Updating (Partial = 0.001; Batch = 1) 0.0156 0.0845 3.374
Online-Updating (Partial = 0.001; Batch = 10) 0.0191 0.0914 0.675
Online-Updating (Partial = 0.001; Batch = 50) 0.0313 0.1353 0.142
Online-Updating (Partial = 0.001; Batch = 100) 0.0515 0.2103 0.137
Online-Updating (Partial = 0.001; Batch = 150) 0.0768 0.2977 0.049
Online-Updating (Partial = 0.001; Batch = 200) 0.0513 0.2033 0.038
Online-Updating (Partial = 0.001; Batch = 500) 0.1022 0.3445 0.017