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This paper presents a dual-model approach for forecasting Indian Lok Sabha elections, combining a micro-level regression model for candidate-specific vote share and a macro-level Monte Carlo simulation for seat allocation. The models utilize data from elections between 1980 and 2019, with the results integrated into an interactive Streamlit dashboard for dynamic analysis. The study demonstrates the effectiveness of the hybrid approach, achieving a high predictive accuracy with XGBoost and providing comprehe

Author

Ayush Domble

Language

EN