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Table 3 The mean of the accuracy on data stream Hyperplane2

From: Comparative study between incremental and ensemble learning on data streams: Case study

  Data-chunk size 500 1000 2000
Classifier number Algorithm    
10 SEA 77.06±0.97 87.91±1.97 87.36±0.78
  AWE 84.94±3.87 85.72±0.53 89.09±.012
20 SEA 86.32±1.21 87.17±0.99 91.15±0.29
  AWE 87.96±0.52 89.27±0.96 91.42±0.26
30 SEA 89.22±1.56 88.49±0.5 90.44±0.08
  AWE 90.36±0.43 89.44±0.46 90.39±0.04
  1. SEA get the optimal accuracy at a 2,000 data chunk size and 20 base classifiers, while AWE algorithm get optimal accuracy at a 2,000 data chunk size and 20 base classifiers.