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Developing an Ensemble Learning Framework Using Machine Learning Methods and its Application in Preventing Road Accidents

Hojjati, Amir Abbas | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52191 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Houshmand, Mohmoud
  7. Abstract:
  8. Road accidents are currently one the main existing problems and a big challenge in Iran that is putting the lives of Iranian citizens in danger. Each accident is the result of a complex interplay between road users, vehicles, roads and environment. One of the main goals of accident data analysis is to identify and determine the main factors of a road accident. The dataset used here was obtained from the road traffic police and is stored in 3 different databases and corresponds to the accidents that happened between years 1390 and 1395 according to the Shamsi calendar. In this thesis, in order to deal with the inherent complexity and heterogeneity of the accident data, we will first introduce the consensus clustering method which uses an appropriate clustering technique in its heart to partition the data, look for similar objects and find structures within the data. After the dataset was partitioned into 3 separated clusters, we use an intra-cluster similarity and inter-cluster distance index to make sure of the clustering quality and then we visulized the cluster in 2 dimensions using a dimensionality reduction method. lastly, after close examination of each cluster. we searched for frequent itemsets within the dataset in order to identify the most important factors leading to an accident
  9. Keywords:
  10. Machine Learning ; Data Mining ; Unsupervised Learning ; Consensus Clustering ; Mixed Data Clustering ; Road Accidents ; Frequent Pattern ; Accident Prevention

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