文件名称:ecoli
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聚类是将数据对象分组成多个簇（Cluster），同一个簇内
部的任意两个对象之间具有较高的
），同一个簇内
部的任意两个对象之间具有较高的 相似度，而属于不同簇
的两个对象间具有较高的
，而属于不同簇
的两个对象间具有较高的 相异度。相异度可以根据描述对
象的属性值计算，对象间的距离是最常采用的度量指标。-Clustering is a data object into a plurality of clusters (the Cluster), with a cluster having between any two objects inside higher), having a high degree of similarity between any two of the same objects inside a cluster, and between two objects belonging to different clusters with high, but between two objects belonging to different clusters have a high degree of difference. Dissimilarity can describe the object' s property values to calculate the distance between objects is the most commonly used metrics.
部的任意两个对象之间具有较高的
），同一个簇内
部的任意两个对象之间具有较高的 相似度，而属于不同簇
的两个对象间具有较高的
，而属于不同簇
的两个对象间具有较高的 相异度。相异度可以根据描述对
象的属性值计算，对象间的距离是最常采用的度量指标。-Clustering is a data object into a plurality of clusters (the Cluster), with a cluster having between any two objects inside higher), having a high degree of similarity between any two of the same objects inside a cluster, and between two objects belonging to different clusters with high, but between two objects belonging to different clusters have a high degree of difference. Dissimilarity can describe the object' s property values to calculate the distance between objects is the most commonly used metrics.
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下载文件列表
AI-knn对UCI上三个数据集实验\AI-knn对ＵＣＩ数据集测试实验\knn-代码和数据集\abalone.data
...........................\............................\................\abalone_knn.cpp
...........................\............................\................\ecoli.data
...........................\............................\................\ecoli_knn.cpp
...........................\............................\................\yeast.data
...........................\............................\................\yeast_knn.cpp
...........................\............................\人工智能实验报告.doc
...........................\............................\knn-代码和数据集
...........................\AI-knn对ＵＣＩ数据集测试实验
AI-knn对UCI上三个数据集实验