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Ensemble Learning In Traffic Incident Detection

EasyChair Preprint no. 3529

6 pagesDate: June 1, 2020


Traffic accident detection is a significant area of research for intelligent transport cadres. Numerous methods have achieved great performance in detecting road accidents. Be that as it may, Strengthening these methods is not acceptable. In a particular context, it is not necessary that by applying a  method is applied against for another generating index, its performance is always getting better it had once even sounded very good in a collection of information. In this research, the main objective s to understand Ensemble learning. Ensemble learning Method are being applied for the betterment in detecting road accidents. SVM & KNN methods individually applied at the start and later on ensembled for desired result achievement. Therefore, a methodology is required to consolidate them for a better final demonstration. The exploratory results are displayed to demonstrate that the best performance is achieved of all thinking methods. The proposed method is better models of each of its consistency.

Keyphrases: detection, ensemble learning, KNN, Navie Base, SVM

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Mehwish Shabbir},
  title = {Ensemble Learning In Traffic Incident Detection},
  howpublished = {EasyChair Preprint no. 3529},

  year = {EasyChair, 2020}}
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