Abstract
The crime is a major problem of community and society which is increasing day by day. Especially in Thailand, crime is a major problem that affects all aspects of the country such as tourism, administration of government and problem in daily life. Therefore, government and private sectors have to understand the several crime patterns for planning, preventing and solving solution of crime correctly. The purposes of this study are to generate a crime model for Thailand using data mining techniques. Data were collected from Dailynews and Thairath online newspapers. The proposed model can be generated by using more feature selection and more classification techniques to different model. Experiments show feature selection with the wrapper of attribute evaluator seems to be an appropriate evaluation algorithm because data set mostly is the best accuracy rate. This improves efficiency in identifying offenders more quickly and accurately. The model can be used for the prevention of crime that will occur in Thailand in the future.
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Sithiprom, T., Srivihok, A. (2016). Comparative Feature Selection of Crime Data in Thailand. In: Berry, M., Hj. Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2016. Communications in Computer and Information Science, vol 652. Springer, Singapore. https://doi.org/10.1007/978-981-10-2777-2_6
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DOI: https://doi.org/10.1007/978-981-10-2777-2_6
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