Generate names using posterior probabilities

栏目: IT技术 · 发布时间: 4年前

内容简介: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 packageInstallThe package

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 serieshere.

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.

If it is people names that you are interested in generating, you are better off using the default training data. However, if you would like to generate names of  items or products (example: pharmaceutical drug names), it is recommended that you build your own training data.

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 non-zero natural number. 

minLength is a numeric. This specifies the minimum number of alphabets in the name. It must be a non-zero natural number .

maxLength is a numeric. This specifies the maximum number of alphabets in the name. It must be a non-zero 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


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