Data Mining Applied to Transportation Mode Classification Problem

Andrea Vassilev

Abstract

The recent increase in processing power and in the number of sensors present in today’s mobile devices leads to a renewed interest in context-aware applications. This paper focuses on a particular type of context, the transportation mode used by a person or freight, and adequate methods for automatically classifying transportation mode from smartphone embedded sensors. This classification problem is generally solved by a searching process which, given a set of design choices relative to sensors, feature selection, classifier family and hyper parameters, etc., find an optimal classifier. This process can be very time consuming, due to the number of design choices, the number of training phases needed for a cross validation step and the time necessary for one training phase. In this paper, we propose to simplify this problem by applying three data mining tools - Principal Component Analysis, Mahalanobis distance and Linear Discriminant Analysis - in order to clean the data, simplify the problem and finally speed up the searching process. We illustrate the different tools on the transportation mode classification problem.

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Paper Citation


in Harvard Style

Vassilev A. (2018). Data Mining Applied to Transportation Mode Classification Problem.In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-293-6, pages 36-46. DOI: 10.5220/0006633300360046


in Bibtex Style

@conference{vehits18,
author={Andrea Vassilev},
title={Data Mining Applied to Transportation Mode Classification Problem},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2018},
pages={36-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006633300360046},
isbn={978-989-758-293-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Data Mining Applied to Transportation Mode Classification Problem
SN - 978-989-758-293-6
AU - Vassilev A.
PY - 2018
SP - 36
EP - 46
DO - 10.5220/0006633300360046