inputWords: (character vector) Vector of character strings for which to calculate the joint probability. Must be in ASCII format.
modelToUse: (character) Which language model to use, supported values: "title", "anchor", "query", or "body" (optional, default: "body")
orderOfNgram: (integer) Which order of N-gram to use, supported values: 1L, 2L, 3L, 4L, or 5L (optional, default: 5L)
Returns
An S3 object of the class weblm. The results are stored in the results dataframe inside this object. The dataframe contains the word sequences and their log(probability).
Examples
## Not run: tryCatch({# Calculate joint probability a particular sequence of words will appear together jointProbabilities <- weblmCalculateJointProbability( inputWords = c("where","is","San","Francisco","where is","San Francisco","where is San Francisco"),# ASCII only modelToUse ="query",# "title"|"anchor"|"query"(default)|"body" orderOfNgram =4L# 1L|2L|3L|4L|5L(default))# Class and structure of jointProbabilities class(jointProbabilities)#> [1] "weblm" str(jointProbabilities, max.level =1)#> List of 3#> $ results:'data.frame': 7 obs. of 2 variables:#> $ json : chr "{"results":[{"words":"where","probability":-3.378}, __truncated__ ]}#> $ request:List of 7#> ..- attr(*, "class")= chr "request"#> - attr(*, "class")= chr "weblm"# Print results pandoc.table(jointProbabilities$results)#> ------------------------------------#> words probability#> ---------------------- -------------#> where -3.378#>#> is -2.607#>#> san -3.292#>#> francisco -4.051#>#> where is -3.961#>#> san francisco -4.086#>#> where is san francisco -7.998#> ------------------------------------}, error =function(err){# Print error geterrmessage()})## End(Not run)