Credal-C4.5: Decision tree based on imprecise probabilities to classify noisy data
作者：
Highlights：
• A new algorithm inspired by C4.5 and imprecise probabilities is defined.
• This algorithm (Credal-C4.5) assumes unreliable data sets when the tree is built.
• Pruning process is also incorporated to Credal-C4.5.
• Several experiments are made to compare algorithms.
• The new method is especially suitable to classify data sets with noise.
摘要
•A new algorithm inspired by C4.5 and imprecise probabilities is defined.•This algorithm (Credal-C4.5) assumes unreliable data sets when the tree is built.•Pruning process is also incorporated to Credal-C4.5.•Several experiments are made to compare algorithms.•The new method is especially suitable to classify data sets with noise.
论文关键词：Imprecise probabilities,Imprecise Dirichlet Model,Uncertainty measures,Credal decision trees,C4.5 algorithm,Noisy data
论文评审过程：Available online 5 February 2014.
论文官网地址：https://doi.org/10.1016/j.eswa.2014.01.017
