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。
This model builds state machine through self-learning from network services and then matches pattern using state machine which has extracted features. Then this model can build response.
该模型对网络会话进行自学习生成状态机，利用经过特征提取的状态机进行模式匹配，进而构造网络会话响应内容。
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