An Intense Study of Machine Learning Research Approach to Identify Toxic Comments
نویسندگان
چکیده
A large number of online public domain comments are usually constructive, but a significant proportion is toxic. The include several errors that allow the machine-learning algorithm to train data set by processing dataset with numerous variety tasks, in method conversion raw previously feeding it Classification models using ML method. In this study, we have proposed classification toxic approach on multilinguistic comment dataset. logistic regression applied classify processed dataset, which will distinguish from non-toxic comments. multi-headed model comprises toxicity (obscene, insult, severe toxic, threat, & identity-hate) or Nontoxicity Estimation. We implemented four (LSTM, GRU RNN, and BiLSTM) detected Python 3, all simple structure can adapt resolution other tasks. problem findings presented aid models. It has been concluded solve challenge effectively, BiLSTM most effective ensure best practicable accuracy.
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ژورنال
عنوان ژورنال: International journal of scientific research in computer science, engineering and information technology
سال: 2022
ISSN: ['2456-3307']
DOI: https://doi.org/10.32628/cseit228391