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

机译:一种使用混合FCM聚类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。 然而,预测的分析非常困难,因为没有关于数据的信息来学习。 本文提出了一种基于使用混合FCM聚类算法的大数据分析的预测模型来解决这些问题。 拟议的模型在没有外部干扰的情况下进行自动分类,并显示了监督和无监督的学习的优势。 我们预计拟议的模型可能会有助于提高各种智能系统中需要使用所提出的框架,Co-Biz的适当预测的自动化标准。

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