Classification method for mixed detection signal in the distributed sensor network

Taking into account the limitations of the distributed sensor networks, a simple and efficient classification method was found. According to the main idea of naïve Bayes classification (NBC) algorithm, a new naïve Bayes classification based on attribute significance (NBCBAS) was proposed. The algorithm inherited the characteristics of NBC algorithm that was simple and fast computation. At the same time, the algorithm made up for the defects of conditional independence assumption. It had high classification accuracy in practice. The characteristics of the NBCBAS met the classification requirements of the mixed detection signal. At last, the NBCBAS was tested on UCI datasets and mixed detection signal datasets. The results illustrate that our algorithm improves the classification performance.