Scholarlink

This research paper aims to improve public safety through the use of crime prediction and its analysis. This research predicts crime hotspots across the country by applying various classifiers such as, Gradient Boosting, Decision Tree, Random Forest, and Support Vector Machine. Data augmentation methods like scaling and SMOTE has been used to help balance class distribution and increase accuracy. Support Vector Machine obtains an accuracy value of 0.96 in our model when SMOTE and feature scaling are used together. This machine learning model provides the particular pattern to predict future crimes which ultimately helps the law enforcement to make the society safe and free of crimes.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Deployment of Machine Learning Model for Predictive Analysis of Rising Crime Trends

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Meghna Halder,
  • Payal Sinha,
  • Digonto Biswas,
  • Tiansheng Yang,
  • Rajkumar Singh Rathore

摘要

This research paper aims to improve public safety through the use of crime prediction and its analysis. This research predicts crime hotspots across the country by applying various classifiers such as, Gradient Boosting, Decision Tree, Random Forest, and Support Vector Machine. Data augmentation methods like scaling and SMOTE has been used to help balance class distribution and increase accuracy. Support Vector Machine obtains an accuracy value of 0.96 in our model when SMOTE and feature scaling are used together. This machine learning model provides the particular pattern to predict future crimes which ultimately helps the law enforcement to make the society safe and free of crimes.