The Application of Feature Selection under Supervised Learning in Liquid Recognition
Year: 2011
Type: conference-paper
Abstract: The problem needed to be solved firstly in liquid identification based on Droplet Fingerprint is feature selection. Feature selection is how to minimize the dimension of feature under the premise of not reducing the classification accuracy. According to the DB index classification criteria and floating search algorithm, this paper proposes an algorithm of feature selection suitable for supervised learning and performs the algorithm in Droplet Fingerprint database. Experimental results show that the algorithm performs better and greatly improves the efficiency of feature selection.
Source: Procedia Engineering
Authors: Song Qing, Luo Yuan, Zou Cunwei, Li Jie
Institution: Beijing University of Posts and Telecommunications
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2091471667