Predictive Analytics in Crime: A Machine Learning Approach

Traditional crime analysis methods are overwhelmed by the ever-growing volume and intricacies of crime data. This research addresses this challenge by proposing a novel system utilizing machine learning to analyze crime data in India. Focusing on “Serious Fraud - Cheating” and “Serious Fraud - Criminal Breach of Trust” across all states, the system tackles the limitations of manual analysis. By integrating k-means clustering and Decision Trees, the system efficiently processes and interprets complex data, achieving high accuracy and precision in identifying patterns. This paves the way for proactive policing strategies, empowering law enforcement to anticipate and prevent future crimes. As technology continues to reshape criminal activity, this system offers a valuable tool for law enforcement agencies to stay ahead of tech-savvy criminals by embracing cutting-edge analytical approaches.