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Please use this identifier to cite or link to this item: http://hdl.handle.net/11173/2846

Title: Solution for The CDMC 2017
Authors: Maruno, Yuki
Hirao, Ayumi
Nishimoto, Mayu
Sakai, Midori
Ohki, Marie
Keywords: Data Mining Competition
APK Malware
Incident Detection
Fraud Detection
Random Forest
Issue Date: 31-Jan-2019
Publisher: 京都女子大学現代社会学部
Abstract: The CDMC 2017 is a competition focusing on real-world problems regarding cybersecurity. We took part in this competition and our team was the first place winner. In this paper, we describe how we solved the following tasks with the provided dataset. We used the Random Forest classifier for all the tasks with the hyperparameter optimization and the feature selection. Experiments showed that our proposed method can obtain an accuracy more than 90% without high computational costs.
URI: http://hdl.handle.net/11173/2846
Appears in Collections:第21号(2019-01-31)

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