Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
Using the processed data we will discuss the basis for clustering genes into sets and discovering gene set features that can be used for diagnostic purposes.
通过使用获得的资料，我们将讨论给凝块基因分组的基础并且探索用于诊断性的目的基因层组特色。
Clustering trajectories as a whole can miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, such as weather forecast and traffic control.
将运动轨迹作为整体聚类会丢失相似子轨迹段，而相似子轨迹段在实际应用中用处很大，如天气预报、交通控制等。
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