Generate names using posterior probabilities
[This article was first published on Rposts.com, and kindly contributed to Rbloggers]. (You can report issue about the content on this page here)
Want to share your content on Rbloggers? click here if you have a blog, or here if you don't.
If you are building synthetic data and need to generate people names, this article will be a helpful guide. This article is part of a series of articles regarding the R package conjurer. You can find the first part of this series here.Want to share your content on Rbloggers? click here if you have a blog, or here if you don't.
Steps to generate people names
1. Installation
Install conjurer package by using the following code.
install.packages("conjurer")
2. Training data Vs default data
The package conjurer provides 2 two options to generate names.

 The first option is to provide a custom training data.
 The second option is to use the default training data provided by the package.
The function that helps in generating names is buildNames. Let us understand the inputs of the function. This function takes the form as given below.
buildNames(dframe, numOfNames, minLength, maxLength)In this function,
dframe is a dataframe. This dataframe must be a single column dataframe where each row contains a name. These names must only contain english alphabets(upper or lower case) from A to Z but no special characters such as “;” or non ASCII characters. If you do not pass this argument to the function, the function uses the default prior probabilities to generate the names.
numOfNames is a numeric. This specifies the number of names to be generated. It should be a nonzero natural number.
minLength is a numeric. This specifies the minimum number of alphabets in the name. It must be a nonzero natural number.
maxLength is a numeric. This specifies the maximum number of alphabets in the name. It must be a nonzero natural number.
3. Example
Let us run this function with an example to see how it works. Let us use the default matrix of prior probabilities for this example. The output would be a list of names as given below.
library(conjurer) peopleNames < buildNames(numOfNames = 3, minLength = 5, maxLength = 7) print(peopleNames) [1] "ellie" "bellann" "netar"Please note that since this is a random generator, you may get other names than displayed in the above example.
4. Consolidated code
Following is the consolidated code for your convenience.
#install latest version install.packages("conjurer") #invoke library library(conjurer) #generate names peopleNames < buildNames(numOfNames = 3, minLength = 5, maxLength = 7) #inspect the names generated print(peopleNames)
5. Concluding remarks
In this article, we have learnt how to use the R package conjurer and generate names. Since the algorithm relies on prior probabilities, the names that are output may not look exactly like real human names but will phonetically sound like human names. So, go ahead and give it a try. If you like to understand the underlying code that generates these names, you can explore the GitHub repository here. If you are interested in what’s coming next in this package, you can find it in the issues section here
To leave a comment for the author, please follow the link and comment on their blog: Rposts.com.
Rbloggers.com offers daily email updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/datascience job.
Want to share your content on Rbloggers? click here if you have a blog, or here if you don't.