Data Mining of Garment Pattern Based on Decision Tree Algorithm

Data Mining of Garment Pattern Based on Decision Tree Algorithm

연구 분야: Databases

학회: EAI International Conference, BigIoT-EDU

With the development of economy, society and culture, the traditional tailor-made clothing has been unable to meet people’s needs for personalization, fit and online customization of clothing. The clothing industry has gradually changed from the original large-scale and standardized production to flexible and personalized customization. Data mining is the process of extracting useful information from data. Data mining is a process of discovering patterns in a large amount of data by applying statistical and computational techniques to data. Decision tree algorithm is such a technology that helps to find patterns in a large amount of data. It uses decision tree to find the best method to classify objects according to their attributes or characteristics. In recent years, the application of advanced technologies, such as computer graphics, digital image processing and artificial intelligence, has brought new opportunities to the garment industry, promoted the mode update of the garment industry, and also promoted the digitalization and intelligence of garment design. Garment digital version is the key problem and research hotspot of garment digital technology. In this paper, the research and analysis of data mining of garment pattern based on decision tree algorithm.