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A cross platform app. Enables people to get information about Law & Order situation (crime status) of a particular location they are visiting to. Built using Dart(Flutter Framework) for front and back end, Firebase as database
This project is intended to find two things: 1) how crime rate at a particular neighborhood influences the listing price of Airbnb. 2) how safe a neighborhood is where the Airbnb listing is located
This repository contains the implementation described in "Developing a Machine Learning Based Support System for Mitigating the Suppression Against Women and Children"
The aim of the work is to explore the data through the use of BigQuery and to predict the number of crimes for a specific year, given the information about the boroughs, the total number of codes for each borough and the different major categories of crime.
Detecting the key reason for crime(manslaughter) happened in 30 years. There's a lot of aspect present in the data published by US government. The data and the finding can be used in any country prospect,if not all but handy few.
Optimized XGBoost model for crime prediction with hyperparameter tuning and feature engineering and preprocessing techniques to achieve a better model performance with a improved F1 score of 0.71 with Accuracy=0.724