Leveraging Regression Techniques to Predict Crime Rates in India: A State-Wise Analysis

This paper studies the influence of socioeconomic and demographic factors on crime rates in India, intending to identify underlying patterns and prediction indices. The study is taken from datasets of reputable organizations such as the National Crime Records Bureau (NCRB) and the Ministry of Statistics and Program Implementation (MoSPI). After preprocessing data, exploratory data analysis (EDA) is done on the data. The analysis applies a variety of linear regression and predictive models that include linear regression, stochastic gradient descent (SGD) regression, and gradient boost regression. Education is significantly correlated with “changes in crime rates” among the various factors studied. Gradient-boosting regression comes out to be the most reliable model, hence making it the best choice for the crime study's policy recommendations. These results try to fill a sizable gap in regional crime studies in India and offer useful data for targeted policy actions. One of the key findings of the study is the impact of education in reducing crime rates.