lof(Rlof)
lof()所属R语言包：Rlof
Local Outlier Factor
局部异常因子
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A function that finds the local outlier factor (Breunig et al.,2000) of the matrix "data" using k neighbours. The local outlier factor (LOF) is a measure of outlierness that is calculated for each observation. The user decides whether or not an observation will be considered an outlier based on this measure. The LOF takes into consideration the density of the neighbourhood around the observation to determine its outlierness. This is a faster implementation of LOF by using a different data structure and distance calculation function compared to lofactor() function available in dprep package. It also supports multiple k values to be calculated in parallel, as well as various distance measures besides the default Euclidean distance.
发现局部异常因子（Breunig等，2000）的矩阵“数据”，使用k近邻的函数。局部异常因子（LOF）是衡量outlierness计算对于每个观测。用户决定是否将被视为一个观察一个离群基于这项措施。的LOF考虑到密度分数周围观察以确定其outlierness。这是一个更快实施LOF相比lofactor()功能dprep包使用不同的数据结构和距离计算功能。它还支持多个并联，以及各种距离措施除了默认的欧几里得距离计算的k值。
用法----------Usage----------
lof(data, k, ...)
参数----------Arguments----------
参数：data
The data set to be explored, which can be a data.frame or matrix
的数据集，以探索，它可以是一个数据框或矩阵
参数：k
The kth-distance to be used to calculate LOFs. k can be a vector which contains multiple k values based on which LOFs need to be calculated.
的第k个被用来计算LOFS距离。 k可以是一个矢量，它包含多个基于哪些LOFS需要计算的k值。
参数：...
The parameters to be passed to distmc() function, specifying the distance measure.
传递给distmc()函数的参数，指定的距离测量。
Details
详细信息----------Details----------
The LOFs are calculated over multiple k values in parallel, and the maximum number of the cpus will be utilised to achieve the best performance.
的lofs多个平行的k值的计算，并的最大数目的的CPU将被利用，以达到最佳的性能。
值----------Value----------
<table summary="R valueblock"> <tr valign="top"><td>lof</td> <td> A matrix with the local outlier factor of each observation as rows and each k value as columns</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD> lof</ TD> <td>一个矩阵的行和每一个k值，每个观察局部异常因子为列</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Yingsong Hu, Wayne Murray and Yin Shan with Strategic Data Mining Team, Department of Human Services, Australian.
参考文献----------References----------
LOF: Identifying density-based local outliers. In Proceedings of the ACM SIGMOD
实例----------Examples----------
#---- Detecting the top outliers using the LOF algorithm [----检测前使用LOF算法的异常值]
#---- with k = 5,6,7,8,9 and 10, respectively----[----与k = 5,6,7,8,9和10，分别----]
data(iris)
df<-data.frame(iris[-5])
df.lof<-lof(df,c(5:10))
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。
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发表于 2012-9-26 23:31:13
