Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications.

寻找隐藏在数据中的信息在理论上是困难的，在实践上也是重要的。为了从数据中发现未知模式，数据挖掘方法源自统计学、机器学习和人工智能，并成功地应用于生物信息学、银行业、零售业和许多其他应用领域。Wang和Fu详细介绍了如何在此类应用中利用模糊神经网络、多层感知器神经网络、径向基函数神经网络、遗传算法和支持向量机的最新技术。