文章目录
- 安装
- 使用
- [amatch & ain](#amatch & ain)
- 延伸:距离计算公式
-
-
- [Hamming distance](#Hamming distance)
- [Longest Common Substring distance](#Longest Common Substring distance)
- [Levenshtein distance (weighted)](#Levenshtein distance (weighted))
- [The optimal string alignment distance dosa](#The optimal string alignment distance dosa)
- [Full Damerau-Levenshtein distance (weighted)](#Full Damerau-Levenshtein distance (weighted))
- [Q-gram distance](#Q-gram distance)
- [Jaccard distance for q-gram count vectors (= 1-Jaccard similarity)](#Jaccard distance for q-gram count vectors (= 1-Jaccard similarity))
- [cosine distance for q-gram count vectors (= 1-cosine similarity)](#cosine distance for q-gram count vectors (= 1-cosine similarity))
- [At last](#At last)
-
安装
R
install.packages('stringdist')
or
bash
git clone https://github.com/markvanderloo/stringdist.git
cd stringdist
bash ./build.bash
R CMD INSTALL output/stringdist_*.tar.gz
使用
The package offers the following main functions:
- stringdist computes pairwise distances between two input character vectors (shorter one is recycled)
- stringdistmatrix computes the distance matrix for one or two vectors
- stringsim computes a string similarity between 0 and 1, based on stringdist
- amatch is a fuzzy matching equivalent of R's native match function
- ain is a fuzzy matching equivalent of R's native %in% operator
- afind finds the location of fuzzy matches of a short string in a long string.
- seq_dist, seq_distmatrix, seq_amatch and seq_ain for distances between, and matching of integer sequences.
stringdist :返回列表
stringdist(
a,
b,
method = c("osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw",
"soundex"),
useBytes = FALSE,
weight = c(d = 1, i = 1, s = 1, t = 1),
q = 1,
p = 0,
bt = 0,
nthread = getOption("sd_num_thread")
)
a :R object (target); will be converted by as.characte
b :R object (source); will be converted by as.character This argument is optional for stringdistmatrix (see section Value).
method :Method for distance calculation.
useBytes :Perform byte-wise comparison
weight :For method='osa' or 'dl', the penalty for deletion, insertion, substitution and transposition, in that order.
When method='lv', the penalty for transposition is ignored.
When method='jw', the weights associated with characters of a, characters from b and the transposition weight, in that order.
Weights must be positive and not exceed 1.
weight is ignored completely when method='hamming', 'qgram', 'cosine', 'Jaccard', 'lcs', or soundex.
q :Size of the q-gram; must be nonnegative. Only applies to method='qgram', 'jaccard' or 'cosine'.
p :Prefix factor for Jaro-Winkler distance. The valid range for p is 0 <= p <= 0.25.
If p=0 (default), the Jaro-distance is returned. Applies only to method='jw'.
bt :Winkler's boost threshold. Winkler's prefix factor is only applied when the Jaro distance is larger than bt. Applies only to method='jw' and p>0.
useNames :Use input vectors as row and column names?
example
注意:String distance functions have two possible special output values.
NA is returned whenever at least one of the input strings to compare is NA .
And Inf is returned when the distance between two strings is undefined according to the selected algorithm.
R
stringdist("bar","foo",method = "lv") #使用的是Levenshtein distance & return 3
stringdist("ba","foo",method = "lv") #使用的是Levenshtein distance & return 3 ,注意这里是不等长的序列
stringdist('fu', 'foo', method='hamming') # 使用的是 Hamming distance & return Inf
stringdistmatrix :返回矩阵
stringdistmatrix(
a,
b,
method = c("osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw",
"soundex"),
useBytes = FALSE,
weight = c(d = 1, i = 1, s = 1, t = 1),
q = 1,
p = 0,
bt = 0,
useNames = c("none", "strings", "names"),
nthread = getOption("sd_num_thread")
)
Arg
example
- 只输入一个vertor:返回一个 dist函数的结果
- 输入两个vector :返回矩阵
amatch & ain
- Function amatch(x,table) finds the closest match of elements of x in table. When multiple equivalent matches are found, the
first match is returned - A call to ain(x,table) returns a logical vector indicating which elements of x were (approximately) matched in table.
- Both amatch and ain have been designed to approach the behaviour of R's native match and %in% functionality as much as possible. By default amatch and ain locate exact matches, just like match.
- This may be changed by increasing the maximum string distance between the search pattern and elements of the lookup table.
amatch仿照R base function match进行设计,通过 参数maxDist控制该函数的行为,如果maxDist 设置的很小其表现近似于 exact match,当 maxDist 设置的比较大时则表现的是approximately match。amtch 与 ain的区别类似于match和 %in%,一个返回元素的index,一个返回TRUE/FALSE。
R
amatch('fu', c('foo','bar')) # return NA
amatch('fu', c('foo','bar'), maxDist=2) # return 1
ain('fu', c('foo','bar')) # return FALSE
ain('fu', c('foo','bar'), maxDist=2) # return TRUE
ain('bar', c('foo','bar')) # return TRUE
ain('bar', c('foo','bar'), maxDist=2) # return TRUE
延伸:距离计算公式
Hamming distance
Longest Common Substring distance
Levenshtein distance (weighted)
The optimal string alignment distance dosa
Full Damerau-Levenshtein distance (weighted)
注意,D~osa~ 和D~dl~的区别主要是最后一个方程式,D~osa~只允许前后相邻的两个字符串置换,D~dl~则允许当前的字符串和其他的字符置换后计算距离
Q-gram distance
Jaccard distance for q-gram count vectors (= 1-Jaccard similarity)
cosine distance for q-gram count vectors (= 1-cosine similarity)
- Jaro distance