文件名称:kmeans
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K-means算法是集简单和经典于一身的基于距离的聚类算法
采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大。
该算法认为类簇是由距离靠近的对象组成的，因此把得到紧凑且独立的簇作为最终目标。(K-means algorithm is a distance based clustering algorithm which is simple and classic.
Distance is used as a similarity evaluation index, that is, the closer the distance between the two objects is, the greater the similarity is.
The algorithm considers that clusters are composed of objects close to each other. Therefore, a compact and independent cluster is the ultimate goal.)
采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大。
该算法认为类簇是由距离靠近的对象组成的，因此把得到紧凑且独立的簇作为最终目标。(K-means algorithm is a distance based clustering algorithm which is simple and classic.
Distance is used as a similarity evaluation index, that is, the closer the distance between the two objects is, the greater the similarity is.
The algorithm considers that clusters are composed of objects close to each other. Therefore, a compact and independent cluster is the ultimate goal.)
相关搜索： kmeans算法
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| kmeans | 0 | 2018-04-08 |
| kmeans\data.txt | 80 | 2018-04-08 |
| kmeans\data.txt~ | 80 | 2014-05-26 |
| kmeans\kmeans.py | 2763 | 2018-04-08 |
| kmeans\kmeans.pyc | 2649 | 2014-05-26 |
| kmeans\kmeans.py~ | 2749 | 2014-05-26 |
| kmeans\test.py | 593 | 2018-04-08 |
| kmeans\test.py~ | 599 | 2014-05-26 |
| kmeans\__pycache__ | 0 | 2018-04-06 |
| kmeans\__pycache__\kmeans.cpython-35.pyc | 2200 | 2018-04-06 |