Application of Errors in Cost-Sensitive Classifications
Zhou Sheng-ming · Journal of Guangxi Normal University · 2011
Aiming at the minimization problem of test costs and misclassification costs on Cost-Sensitive learning,application of errors in classifications are discussed.A kind of decision trees and test strategies with thresholds are proposed.There are errors on both Cost-Sensitive classifications resalted from methods of tests and equipment accuracy and evaluating misclassification.In addition,many classification problems are not required to achieve one hundred percent classification accuracy.The boundaries of these errors are regarded as a kind of threshold values.The establishment of decision trees is simplified and the design of test strategies and the classification efficiency are improved by using these threshold values.