Crime Analytics
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Overview:
The data used here is downloaded from the free source entity regarding the crimes happening in UAE.
An additional Column was added: Gender (0-> Female, 1-> Male)
Business Challenge or Problem:
- Data Manipulation
- Prediction – What are the chances that the convict of the same gender will commit the same crime?
Working Solution:
Crime by Emirates- Input File
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Types of Crime -Input File
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Each crime is allotted a score which helps in the calculation of black points
Emirates List -Input File
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Data Merging, Joining and Manipulation
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- The input files have been merged together as it has the same format.
- The scores of emirate list and Type of crimes ae joined based on the keys-emirate and crime name respectively.
- Crime index- Denotes the number of black points which will be added to the account holder of the convict- is calculated by the value multiplied with the crime and emirate score and 100 to get the no of black points generated.
Prediction:
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Using boosted model,
The Target specified:
- Gender
Predictors specified:
- Type of crime
- Emirate
- Value and crime index
- Year
X predicts the % of chance of that gender committing the type of crime the next time.
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For e.g., In the year 2000, a male committed crime against the firearms law in Abu Dhabi, and that led to 18 black points in his account. He is 51% likely to commit the same crime in future.
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