MACHINE LEARNING APPROACH TO CLASSIFY THE SENTIMENT VALUE OF NATURAL LANGUAGE PROCESSING IN TELUGU DATA

Natural Language Processing (NLP) is a computer software utilized in big information programs to specify the consumer review additionally, it's a major a part of AI. as a result NLP strategy is processed with numerous languages because the language is differing from kingdom to country. Further more, sentiment analysis in NLP is superior in lots of programs and various languages to evaluate the sentiment . but part of speech specification for distinctive language is simply too tough. to overcome this trouble the contemporary studies aimed to expand a singular Evolving C4.5 machine mastering with Spider Monkey Optimization (EC4.5-ML-SMO) to categorise the sentiment evaluation in Telugu language effectively. Furthermore, the fitness feature of SMO more desirable the accuracy of sentiment class in Telugu dataset. Subsequently, the effectiveness of proposed module is evaluated with current existing works and attained better end result via reaching better class accuracy rate.