Analysing stop and search of Metropolitan police in the UK

Abstract

Stop and search by the Metropolitan police is always a significant power for protecting the public fighting against crimes and keeping streets free from danger. This study aims to analyse the outcome of the stop and search of Metropolitan police using secondary data collected from the London store data website.

 In addition, this project will help to identify the best model to analyze this dataset among decision trees and logistic regression with measures of accuracy, precision, and recall score. After, K-Mode was used to group data items into a specified number of clusters considering their features. Furthermore, the ROC curve was plotted to show the performance of every model. In analysis, it was found that logistic regression is better compared to other models due to the different parameters stated below, and K-Mode showed that the male gender was arrested many times more than the female gender.

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