KashEnsem-R: a transformer-enhanced stacked ensemble framework for sentiment classification in Kashmiri

Key Points

• This research aims to develop an effective framework for sentiment classification in the Kashmiri language using advanced AI methods.
• Developed the KashEnsem-R framework incorporating transformer models and stacked ensemble techniques.
• Evaluated the framework's performance on sentiment classification tasks within the Kashmiri language.
• Achieved increased accuracy rates in sentiment classification compared to traditional methods.
• Demonstrated superior performance metrics, enhancing understanding of sentiments in the Kashmiri language.