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 1 | # Predicting the Road Traffic Accident Severity
 2 | 
 3 | ![image](https://github.com/nishantsingha13/Traffic-injury-detection/assets/103675762/cfcf1173-f741-4ead-94f2-aaaa70811e23)
 4 | 
 5 | ### Dataset Description
 6 | The data set is collected from online website. The data set has been prepared from manual records of road traffic accidents of the year 2017-20. 
 7 | It has 32 features and 12316 instances of the accident. Then it is preprocessed and for identification of major
 8 | causes of the accident by analyzing it using different machine learning classification algorithms.
 9 | 
10 | #### Conclusion
11 | Given specific parameters, a model was developed to predict the severity of accidents, categorized as:
12 | #### 1=normal 
13 | #### 2=serious
14 | #### 3=dangerous
15 | Machine learning algorithms, logistic regression and decision tree, were employed for this task. 
16 | The logistic regression model achieved an accuracy of 91.67%.
17 | Decision tree model achieved a slightly lower accuracy of 83.33%. 
18 | These accuracies indicate the effectiveness of the models in predicting accident severity, with logistic regression outperforming the decision tree approach in this scenario
19 | 


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