Abstract
We propose a conjunction rule based classification technique that has good classification performance, is simple, automatically identifies important attributes, and is extremely fast. Due to these properties the classifier is most suitable for “big”/streaming data. Empirical study, using multiple datasets, shows that time complexity, compared with other classifiers, is faster by several factors, especially for large number of attributes without sacrificing performance.
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Xiao, Y., Mehrotra, K.G., Mohan, C.K. (2015). Efficient Classification of Binary Data Stream with Concept Drifting Using Conjunction Rule Based Boolean Classifier. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_44
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DOI: https://doi.org/10.1007/978-3-319-19066-2_44
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