Density Based Mode Within Radius and Its Application to EEG based Emotion Recognition
Statistical parameters such as center points are widely used to represent patterns in machine learning. There are three popular center points: mean, median, and mode. Mean and median are pervasively used as features to represent patterns, but mode is not because of its weakness. One of the major pro...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2021-04-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Subjects: | |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/128558 |
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| Summary: | Statistical parameters such as center points are widely used to represent patterns in machine learning. There are three popular center points: mean, median, and mode. Mean and median are pervasively used as features to represent patterns, but mode is not because of its weakness. One of the major problems in the conventional definition of mode occurs when the distribution is multimodal with tied multiple maximum points. Hence, in this paper we propose a modified version of mode, which utilizes the density within a radius. The effectiveness of proposed mode is demonstrated in the emotion recognition application using the Electroencephalogram (EEG). An experimental result of amalgamating statistical parameters with a new modified parameter suggests the superiority of the proposed statistical parameter over the traditional measures. |
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| ISSN: | 2334-0754 2334-0762 |