partition.kmeans(sperrorest)
partition.kmeans()所属R语言包：sperrorest
Partition samples spatially using k-means clustering of the coordinates
分区样本空间的坐标使用k-means聚类
译者：生物统计家园网 机器人LoveR
描述----------Description----------
partition.kmeans divides the study area into irregularly shaped spatial partitions based on k-means (kmeans) clustering of spatial coordinates.
partition.kmeans将研究区域划分为形状不规则的空间分区的基础上（kmeans）的k-means聚类的空间坐标。
用法----------Usage----------
partition.kmeans(data, coords = c("x", "y"), nfold = 10,
repetition = 1, seed1 = NULL, return.factor = FALSE,
balancing.steps = 1, order.clusters = TRUE, ...)
参数----------Arguments----------
参数：coords
vector of length 2 defining the variables in data that contain the x and y coordinates of sample locations
向量，长度为2data包含的x和y坐标的样本的位置定义的变量在
参数：nfold
number of cross-validation folds, i.e. parameter k in k-means clustering
交叉验证褶皱的数量，即参数k的k-means聚类
参数：balancing.steps
if >1, perform nfold-means clustering balancing.steps times, and pick the clustering that minimizes the Gini index of the sample size distribution among the partitions. The idea is that 'degenerate' partitions will be avoided, but this also has the side effect of reducing variation among partitioning repetitions. More meaningful constraints (e.g., minimum number of positive and negative samples within each partition should be added in the future.
如果>1，执行nfold-means聚类balancing.steps倍，并挑选聚类，最大限度地减少分区之间的样品的粒度分布的基尼系数。我们的想法是，堕落分区，将可避免，但是这也有副作用，减少分区重复之间的差异。应当在将来添加更多的有意义的限制（例如，在每个分区中的阳性和阴性样品的最小数目。
参数：order.clusters
if TRUE, clusters are ordered by increasing x coordinate of center point
如果TRUE，聚类是有序的通过增加中心点的x坐标
参数：...
additional arguments to kmeans
额外的参数kmeans
参数：data
data.frame containing at least the columns specified by coords
data.frame的至少包含列指定的coords
参数：repetition
numeric vector: cross-validation repetitions to be generated. Note that this is not the number of repetitions, but the indices of these repetitions. E.g., use repetition=c(1:100) to obtain (the 'first') 100 repetitions, and repetition=c(101:200) to obtain a different set of 100 repetitions.
数字向量：交叉验证的重复产生。注意，这是不重复的次数，但这些重复的指数。例如，使用repetition=c(1:100)（“第一个”）取得100个重复，和repetition=c(101:200)获得一组不同的重复100次。
参数：seed1
seed1+i is the random seed that will be used by set.seed in repetition i (i in repetition) to initialize the random number generator before sampling from the data set.
seed1+i是随机的种子，将用于set.seed重复i（irepetition）采样前的数据初始化随机数生成器设置。
参数：return.factor
if FALSE (default), return a represampling object; if TRUE (used internally by other sperrorest functions), return a list containing factor vectors (see Value)
如果FALSE（默认），返回一个represampling对象，如果TRUE（内部使用其他sperrorest功能的），返回一个list因子矢量（见值）
值----------Value----------
A represampling object, see also partition.cv for details.
Arepresampling对象，请参阅partition.cv的详细信息。
注意----------Note----------
Default parameter settings may change in future releases.
在将来的版本中，默认的参数设置可能会改变。
参考文献----------References----------
Detecting rock glacier flow structures using Gabor filters and IKONOS imagery. Submitted to Remote Sensing of Environment.
agriculture: Management of spatial information. In 13th International Conference on Information Processing and Management of Uncertainty, IPMU 2010; Dortmund; 28 June - 2 July 2010. Lecture Notes in Computer Science, 6178 LNAI: 350-359.
参见----------See Also----------
sperrorest, partition.cv, partition.disc, partition.tiles, kmeans
sperrorest，partition.cv，partition.disc，partition.tiles，kmeans
实例----------Examples----------
data(ecuador)
resamp = partition.kmeans(ecuador, nfold = 5, repetition = 1:2)
plot(resamp, ecuador)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
|
发表于 2012-9-30 15:03:29
