求翻译：想获得好的聚类效果，首先要解决的就是距离的度量问题，传统的层次聚类算法大多仅仅依赖欧式距离进行度量，没有考虑数据点周围对象的分布情况，以及数据结构不同对聚类结果的影响，很显然聚类准确度往往不尽人意。是什么意思？

Want to get a good clustering effect , we must first solve the problem is to measure the distance , the traditional hierarchical clustering algorithms are dependent on only the Euclidean distance measure , does not consider the data in different distribution points around the object , and the data s

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Wants to obtain the good cluster effect, first must solve is the distance measure question, the traditional level cluster algorithm relies on the western-style distance to carry on the measure mostly merely, had not considered around the data point the object distributed situation, as well as the co

Want to get a good clustering effect, we must first solve is the measurement of the distance, most of the traditional hierarchical clustering algorithm depend only on Euclidean distance measure does not take into account the distribution of data points around objects, effects of different clustering

正在翻译，请等待...