Cost-sensitive deep forest for price prediction

• Main Authors: MA, Chao, LIU, Zhenbing, CAO, Zhiguang, SONG, Wen, ZHANG, Jie, ZENG, Weiliang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Cost-sensitive Deep Forest;Ensemble Deep Learning;Price Prediction;Modified K-means; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8122; https://ink.library.smu.edu.sg/context/sis_research/article/9125/viewcontent/Cost_sensitive_deep_forest_for_price_prediction.pdf
• Institution: Singapore Management University

For many real-world applications, predicting a price range is more practical and desirable than predicting a concrete value. In this case, price prediction can be regarded as a classification problem. Although deep forest is recognized as the best solution to many classification problems, a crucial...