Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The aim of the current study is to compare the effect of three different feature types for age-based categorization of short texts as average 85 words per author. Besides widely used word and character n-grams, text readability features are proposed as an alternative. By readability features  mean different relative ratios of text elements as characters per word, words per sentence, etc. Support Vector Machines, Logistic Regression, and Bayesian algorithms re used to build models. Most effective features re readability features and character n-grams. Model generated by Support Vector Machine and combined feature set yield to f-score 0.968. Age prediction application was built using a model with readability features.
['Avar Pentel']
I am writing a research paper on a idea Effect of different feature types on age based classification of short texts
[{"from": "human", "value": "I am writing a research paper on a idea Effect of different feature types on age based classification of short texts"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The aim of the current study is to compare the effect of three different feature types for age-based categorization of short texts as average 85 words per author. Besides widely used word and character n-grams, text readability features are proposed as an alternative. By readability features  mean different relative ratios of text elements as characters per word, words per sentence, etc. Support Vector Machines, Logistic Regression, and Bayesian algorithms re used to build models. Most effective features re readability features and character n-grams. Model generated by Support Vector Machine and combined feature set yield to f-score 0.968. Age prediction application was built using a model with readability features."}]