Role of a Social Activist Towards Poverty Reduction

Abstract

Poverty rates are not a taboo subject. In actuality, it occurs in every nation on earth when governments and social activists fight to lower the poverty rate. Unfortunately, there are a number of problems with the current methods for identifying the appropriate targeted underprivileged population to whom financial aid should be given, including data openness and inaccurate, redundant, or imbalanced data. The goal of this research set out to determine the ways in which social activists in india have contributed to the decline of poverty. The following were the goals of the study: to determine the influence of social activists in enhancing livelihoods in order to forecast a decrease in poverty in india and to evaluate social activists' impact on india's efforts to reduce poverty through forecasting. Several feature engineering and data cleaning pre-processing methodologies are used in this research's machine learning approach, which is then followed by three different regression algorithms for predictive analysis. Using the costa rican household poverty dataset, the proposed machine learning model is tested. According to the experimental results, the random forest regressor outperforms the other two regression models tested in terms of r2 and rmse score, scoring 0.8355 well-fitted and 0.148 error rates, respectively.