Analysis of college students’ canteen consumption by broad learning clustering: A case study in Guangdong Province, China

• DOI: 10.1371/journal.pone.0276006
• Publication Date: 2022-10-13T17:48:52Z
• Authors: Chun Yang; Hongwei Wen; Darui Jiang; Lijuan Xu; Shaoyong Hong
• Keywords: Consumption

Investigation on college students’ consumption ability help classify them as from rich or relative poor family, thus to distinguish the students who are in urgent need for government’s economic support. As canteen is main part of expenses students, we proposed adjusted K-means clustering methods discrimination at different levels. To improve accuracy, a broad learning network architecture was built up extracting informative features records. A fuzzy transformed technique combined extend candidate range identifying implicit variables single type data. Then, model fully trained. We specially designed train parameters an iterative tuning mode, order find precise properties that reflect characteristics. The selected feature further delivered establish model. For case study, framework combining with method applied data Guangdong province, China. Results show most optimal structured 14 hidden nodes, training and testing results appreciating. indicated feasible into levels by analyzing their data, so able financial aid.