Crime Prediction Using Random Forest Model

The most serious issue in present scenario is crime, which disrupts the people’s lives. The crime will not occur not only in certain time of human lives but it will occur at any time in person’s life, whether they are travelling home from work or going on trip etc. In terms of public safety, crime prediction is required. We can predict the crimes using Random Forest Model. This model will help the authorized officers do their work efficiently as well as effectively so that they can avoid the crime before it occurs. Depending on the quality of the data, the crime prediction accuracy can vary differently. The amount of crimes that occur can be decreased with effective crime prediction. Models such as Polynomial and Linear Regressions limits in capturing intricacy of crime data , however Regression model demonstrates encouraging results. The main significance that we need to keep in mind is that selecting suitable machine learning methods for tasks related to prediction of crimes.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-03
DOI
https://doi.org/10.5281/zenodo.15331868
Primary Topic
Crime Patterns and Interventions
Type
article
Field-Weighted Citation Impact
0.00
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article

Crime Prediction Using Random Forest Model

Zenodo (CERN European Organization for Nuclear Research)
Crime Patterns and Interventions
article

Crime Prediction Using Random Forest Model

article en

Abstract

The most serious issue in present scenario is crime, which disrupts the people’s lives. The crime will not occur not only in certain time of human lives but it will occur at any time in person’s life, whether they are travelling home from work or going on trip etc. In terms of public safety, crime prediction is required. We can predict the crimes using Random Forest Model. This model will help the authorized officers do their work efficiently as well as effectively so that they can avoid the crime before it occurs. Depending on the quality of the data, the crime prediction accuracy can vary differently. The amount of crimes that occur can be decreased with effective crime prediction. Models such as Polynomial and Linear Regressions limits in capturing intricacy of crime data , however Regression model demonstrates encouraging results. The main significance that we need to keep in mind is that selecting suitable machine learning methods for tasks related to prediction of crimes.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 46%
Crime Patterns and Interventions
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