Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  defined a set of quantifiable features for authorship categorization.  performed our experiments on public domain literature — all books analyzed re obtained in plain text format through Project Gutenberg's online repository of classic books.  tested three machine learning algorithms: Artificial Neural Network, Naive Bayes Classifier, and Support Vector Machine with our features.  found that certain features, such as punctuation and various suffixes result in a higher accuracy. In addition, the Support Vector Machine classifier produces repeatedly higher accuracies than other classifiers and seems to be a far superior method of classification in terms of authorship categorization.
['Tudor Boran', 'John Voss', 'Shafaeat Hossain']
I am writing a research paper on a idea Authorship categorization of public domain literature
[{"from": "human", "value": "I am writing a research paper on a idea Authorship categorization of public domain literature"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  defined a set of quantifiable features for authorship categorization.  performed our experiments on public domain literature \u2014 all books analyzed re obtained in plain text format through Project Gutenberg's online repository of classic books.  tested three machine learning algorithms: Artificial Neural Network, Naive Bayes Classifier, and Support Vector Machine with our features.  found that certain features, such as punctuation and various suffixes result in a higher accuracy. In addition, the Support Vector Machine classifier produces repeatedly higher accuracies than other classifiers and seems to be a far superior method of classification in terms of authorship categorization."}]