extVal(validator)
extVal()所属R语言包:validator
External Validation Indices
外部验证指数
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function is calculating the values of certain external validation indices. The values compare the predicted cluster assignment with their true cluster labelling existing in the data.
此功能是计算的某些外部验证指标值。的值比较,与自己的真实群聚现有的数据预测簇分配。
用法----------Usage----------
extVal(x, y, index = "all")
参数----------Arguments----------
参数:x
Vector of the true cluster assignment
矢量的真实簇分配
参数:y
Vector of the cluster assignment, which has to be compare with the true one
矢量的聚类的分配,其具有要与真正的一个比较
参数:index
The external indices, which are calculated: "Hamann", "Czekanowski", "Kulczynski", "McConnaughey", "Peirce", "Wallace1", "Wallace2", "Gamma", "Sokal1", "Fager", "Sokal2", "Sokal3", "Gower", "Roger", "Kruskal", "Pearson", "Rand", "Jaccard", "Folkes", "Russel", and "all".
外部指标,计算:“Hamann”,“Czekanowski”,“Kulczynski”,“McConnaughey”,“Peirce”“ Wallace1“,”Wallace2“,”Gamma“,”Sokal1“,”Fager“,”Sokal2“,”<X “,”Sokal3“,”Gower“,”Roger“,”Kruskal“,”Pearson“,”Rand “,”Jaccard“,”Folkes“,和”Russel“。
Details
详细信息----------Details----------
The data points are counted in a pairwise co-assignment. Given two partitions named C1 and C2, the quantities a, b, c and d are computed for the pairs of the data points xi and xj and their cluster assignments. The numbers a and d are counted as the agreements between the two cluster partitions C1 and C2, whereas b and c are the disagreements of these two partitions:
在成对的共同转让的数据点进行计数。鉴于两个分区命名为C1和C2,用于对数据点xi和xj和它们的聚类分配的数量,b,c和d的计算。 A和D都算作两个聚类分区C1和C2之间的协议,而b和c的分歧,这两个分区:
</table> Then, the external indices are computed with these values:
</ TABLE>接着,外部指数计算这些值:
</td> </tr> </table>
</ TD> </ TR> </ TABLE>
值----------Value----------
This function returns a vector with the external validation indices.
这个函数返回一个矢量与外部的验证指标。
(作者)----------Author(s)----------
Marcus Scherl
参考文献----------References----------
Ahmed N Albatineh, Magdalena Niewiadomska-Bugaj, and Daniel Mihalko On similarity indices and correction for chance agreement.
实例----------Examples----------
#require(mlbench)[要求(mlbench)]
#require(flexclust)[要求(flexclust)]
x <- mlbench.2dnormals(500, 3)
cl <- kcca(x$x, 3)
pred <- predict(cl, x$x)
extVal(pred, x$class)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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