Feature Selections Using Minimal Redundancy Maximal Relevance Algorithm for Human Activity Recognition in Smart Home Environments

المؤلفون المشاركون

Tang, Pei
Fang, Hongqing
Si, Hao

المصدر

Journal of Healthcare Engineering

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-11-29

دولة النشر

مصر

عدد الصفحات

13

الموضوع الرئيسي

الصحة العامة
الطب البشري

الملخص EN

In this paper, maximal relevance measure and minimal redundancy maximal relevance (mRMR) algorithm (under D-R and D/R criteria) have been applied to select features and to compose different features subsets based on observed motion sensor events for human activity recognition in smart home environments.

And then, the selected features subsets have been evaluated and the activity recognition accuracy rates have been compared with two probabilistic algorithms: naïve Bayes (NB) classifier and hidden Markov model (HMM).

The experimental results show that not all features are beneficial to human activity recognition and different features subsets yield different human activity recognition accuracy rates.

Furthermore, even the same features subset has different effect on human activity recognition accuracy rate for different activity classifiers.

It is significant for researchers performing human activity recognition to consider both relevance between features and activities and redundancy among features.

Generally, both maximal relevance measure and mRMR algorithm are feasible for feature selection and positive to activity recognition.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Fang, Hongqing& Tang, Pei& Si, Hao. 2020. Feature Selections Using Minimal Redundancy Maximal Relevance Algorithm for Human Activity Recognition in Smart Home Environments. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1186596

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Tang, Pei…[et al.]. Feature Selections Using Minimal Redundancy Maximal Relevance Algorithm for Human Activity Recognition in Smart Home Environments. Journal of Healthcare Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1186596

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Fang, Hongqing& Tang, Pei& Si, Hao. Feature Selections Using Minimal Redundancy Maximal Relevance Algorithm for Human Activity Recognition in Smart Home Environments. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1186596

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1186596