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A prediction model based on Big Data analysis using hybrid FCM clustering

机译:基于混合FCM聚类的基于大数据分析的预测模型

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The prediction models based on unsupervised learning are fast and need not have labeled data. However, the analysis for prediction is quite difficult, since no information about the data is given to us for learning. This paper proposes a prediction model based on Big Data analysis using hybrid FCM clustering algorithm to address these problems. The proposed model conducts automatic classification without external interference and shows the advantages of both supervised and unsupervised learning. We expect that the proposed model might contribute to enhance automation standards in various intelligent systems which need appropriate prediction using proposed framework, Co-Biz.
机译:基于无监督学习的预测模型是快速的,不需要标记数据。但是,由于没有将有关数据的信息提供给我们进行学习,因此用于预测的分析非常困难。为解决这些问题,本文提出了一种基于大数据分析的预测模型,该模型使用混合FCM聚类算法。所提出的模型进行自动分类而没有外部干扰,并显示了有监督和无监督学习的优点。我们希望所提出的模型可能有助于提高各种智能系统中的自动化标准,这些智能系统需要使用所提出的框架Co-Biz进行适当的预测。

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