To conduct our sampling designs in an adaptive manner we start with a small seed dataset. Initial probabilities are obtained from the seed dataset and then entropy values are extracted. Then the algorithm samples feature observations based on the three different schemes. Levels of uncertainty (entropies) for all of the items are updated based on what have been sampled so far. This process is repeated until the final sampling criterion, which in this study is to reach a fixed number of observations. Figure 4, shows a simple flowchart of the algorithm. In this study 3 different sizes for the seed dataset are: 2, 4 and 8 records.
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