# Integrating Machine Learning Techniques for Enhanced Safety and Crime Analysis in Maryland
## 3 Methodology
### Input Variables  
This section delineates the criteria for selecting a comprehensive range of input variables, which are then utilized to assess and predict crime rates across various Maryland counties. These variables are segmented into demographic, economic, and crime-specific indicators, each of which is critical for crafting a nuanced analysis of crime dynamics. The variables included here are outlined in Appendix A (Table A1) and were chosen through a systematic review of the literature, which pinpointed those factors frequently associated with crime trends and their predictive power. This selection includes demographic data such as population metrics and economic indicators like median household income and unemployment rates, along with crime-specific rates like murder, rape, and robbery. These are calculated using standardized formulas to ensure consistency and comparability across different geographic regions and time periods.  
The criteria for variable selection were anchored on their established relevance in previous research, providing a robust analytical base that leverages proven predictors of crime. This structured approach enhances the scalability and applicability of our analysis across diverse datasets, minimizing manual selection efforts. Future datasets can utilize automated algorithms that select variables based on their statistical significance and predictive validity, streamlining the variable inclusion process.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Data Source** & **Description** & **Years Covered** & **Relevance** \\ \hline
[41] & Violent and property crime rates by municipality in Maryland. & 2000–Present & Offers a longitudinal view of crime trends across Maryland’s regions. \\ \hline
[42] & Data on cumulative reductions in violent crime, illustrating the effectiveness of crime reduction initiatives. & 2006–2014 & Measures the success of crime prevention initiatives over time. \\ \hline
[43] & Detailed crime data for Montgomery County, MD. & 1975–Present & Provides regional insights and trends within Montgomery County. \\ \hline
[44] & Detailed property and violent crime data for Anne Arundel County. & 1975–Present & Offers a focused view of historical crime trends in a specific county. \\ \hline
[45] & Statewide totals for violent and property crime across Maryland. & 2006–Present & Provides a macro view of statewide crime trends. \\ \hline
[46] & Data on domestic violence incidents across Maryland. & 2010–2020 & Assesses trends in domestic violence as a subset of violent crimes. \\ \hline
[47] & Recent crime incidents in Prince George’s County. & July 2023–Present & Provides up-to-date crime data for the current analysis. \\ \hline
[48] & Data on population growth, median household income, unemployment rates, and poverty levels for Maryland counties. & 2012–2022 & Provides socio-economic context for crime analysis, highlighting the correlations between crime rates and economic factors. \\ \hline
[49] & Rates of murder, rape, robbery, aggravated assault, breaking and entering, larceny theft, and motor vehicle theft across Maryland. & 1975–Present & Provides granular crime rate data for specific crime types, allowing for detailed statistical analysis and prediction modeling. \\ \hline
[50] & Data on domestic and international migration trends in Maryland. & 2001–2022 & Explores how migration patterns impact crime rates by altering regional demographics and socio-economic conditions. \\ \hline \hline \end{tabular}
\end{table}
Table 1: Data sources.