Prediction System of Traffic collisions in Toronto
This project involves building a predictive model using the Killed or Seriously Injured (KSI) collision dataset provided by the Toronto Police Service. The goal is to predict whether an individual involved in a collision is fatal or non-fatal based on their specific information.
The main challenge of this project lies in the dataset itself, as the fatal or non-fatal classification is based on the overall accident rather than the individual person involved.
In a traffic accident, multiple individuals may be involved, each associated with different vehicles. However, how does the dataset classify an accident as fatal or non-fatal? Typically, it is categorized as fatal if at least one person dies. If we aim to build a model to predict whether an individual’s outcome is fatal or non-fatal, we need to exclude all individuals incorrectly marked as fatal. These individuals are labeled as such solely because the accident was fatal, even though they themselves did not die.
