Then it construct data warehouse and make the multi-dimensional data set of customers category, service type and time and so on.

然后构建数据仓库，建立以客户群类别、业务种类、时间等为维度的多维数据集。

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And based on the experimental results of multi-dimensional data clustering, anomaly detection matrix is determined through identifying the training sample set and the machine self-learning.

然后根据对多维数据聚类的实验分析结果，通过对样本集的训练进行标识和机器自学习过程来判别异常检测矩阵。

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