Abstract
Abstract For high-dimensional water treatment plant data sets and a single rough classifier's weak classification ability for data sets with many classes, a new computing approach, termed CMBMRCS (water treatment plant Classification Model Based on Multiple Rough Classifier Systems), is proposed. First, by combing rough sets theory, some subset of attributes is selected. Then, each simplified data set establishes a group of rough classifiers. Finally, the water treatment plant data classification result is obtained according to the absolute majority voting strategy. The experimental results illustrate the effectiveness of the proposed methods.
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