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article · Journal of Computational and Theoretical Nanoscience · 2019

Road Accident Data Analysis: Data Preprocessing for Better Model Building

Salahadin Seid Yassin, Pooja .

Cited by 17Abstract and details only

Abstract

In this study we focused on the relationship between preprocessing and model accuracy. The performance of the Machine learning techniques depends on the quality of the data set. Preprocessing is not only advantageous but it is very necessary and a preliminary work in predicting model. As a result, experiments discovered that preprocessed techniques increased performance for model building. To see the performance preprocessing support vector machine is applied before preprocessing and after preprocessing. Its model accuracy increased from 68.7% to 88.5%.

Cite this paper

APA 7

Yassin, S. S., & ., P. (2019). Road Accident Data Analysis: Data Preprocessing for Better Model Building. Journal of Computational and Theoretical Nanoscience, 16(9), 4019–4027. https://doi.org/10.1166/jctn.2019.8288

MLA 9

Yassin, Salahadin Seid, and Pooja . “Road Accident Data Analysis: Data Preprocessing for Better Model Building.” Journal of Computational and Theoretical Nanoscience, vol. 16, no. 9, 2019, pp. 4019–27, https://doi.org/10.1166/jctn.2019.8288.

Chicago

Yassin, Salahadin Seid, and Pooja . 2019. “Road Accident Data Analysis: Data Preprocessing for Better Model Building.” Journal of Computational and Theoretical Nanoscience 16 (9): 4019–27. https://doi.org/10.1166/jctn.2019.8288.

Harvard

Yassin, S.S. and ., P. (2019) ‘Road Accident Data Analysis: Data Preprocessing for Better Model Building’, Journal of Computational and Theoretical Nanoscience, 16(9), pp. 4019–4027. Available at: https://doi.org/10.1166/jctn.2019.8288.

BibTeX
@article{yassin2019road,
  title = {{Road Accident Data Analysis: Data Preprocessing for Better Model Building}},
  author = {Yassin, Salahadin Seid and ., Pooja},
  journal = {Journal of Computational and Theoretical Nanoscience},
  volume = {16},
  number = {9},
  pages = {4019--4027},
  year = {2019},
  doi = {10.1166/jctn.2019.8288}
}

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