Artificial Neural Networks and Their Applications in Business

Knowledge discovery in datasets (KDD), the process of finding non-obvious patterns or trends in datasets primarily to assist in understanding complicated systems (Mannila, 1996), leveraging computational pattern recognition methods to predict, describe, classify, group, and categorization data (Jain, Duin, & Mao, 2000). The nonlinearity of ANNs lend to modeling complex data structures; however, this also results in ANNs being complex and opaque to many users (Weckman, et al., 2009). While ANNs see application in business applications, some hesitation and misconceptions appear due to the ‘black-box’ nature of ANNs (Dewdney, 1997); hence traditional statistical-based models are far more used in practice. Although some interpretability aspects exist when applying ANNs (de Marchi, Gelpi, & Grynaviski, 2004), it should be noted that the interpretability of ANNs is subjective relative to other commonly used tools.

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