文件名称:cluster_by_distances
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通过欧几里德距离对三维空间内的数据点进行聚类:
从文件读入三列表示坐标的数据进行聚类。按项目总数和组数平均划分。首先计算两两之间的距离,选出最近的两个点,再按距离由小到大排序,找出距这两个点最近的若干个点。
除去这些点后对其余的点重复进行上述操作。-By Euclidean distance on three-dimensional space, clustering of data points: from the file read into the three coordinates of the data indicated that cluster. According to the average number of total number of projects and group division. First, calculate the distance between 22 to elect the nearest two points, and then from small to large order to identify these two points away from a number of recent points. After removing these points the rest of the point of repeating to carry out such operations.
从文件读入三列表示坐标的数据进行聚类。按项目总数和组数平均划分。首先计算两两之间的距离,选出最近的两个点,再按距离由小到大排序,找出距这两个点最近的若干个点。
除去这些点后对其余的点重复进行上述操作。-By Euclidean distance on three-dimensional space, clustering of data points: from the file read into the three coordinates of the data indicated that cluster. According to the average number of total number of projects and group division. First, calculate the distance between 22 to elect the nearest two points, and then from small to large order to identify these two points away from a number of recent points. After removing these points the rest of the point of repeating to carry out such operations.
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mainprog.c
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