@article{MAKHILLAJIT20076115470,
    title = {A New Cost-Sensitive Decision Tree with Missing Values},
    journal = {Asian Journal of Information Technology},
    volume = {6},
    number = {11},
    pages = {1083-1090},
    year = {2007},
    issn = {1682-3915},
    doi = {ajit.2007.1083.1090},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2007.1083.1090},
    author = {Xingyi Liu},
    keywords = {Cost-sensitive,decision tree,missing values,misclassification cost},
    abstract = {Cost-sensitive learning is popular during the process of classification. Most researches focus on two costs for building cost-sensitive decision trees, such as, misclassification costs, test costs. In this  study, a novel splitting attributes criterion is proposed firstly. And a test strategy combining discount costs for decreasing the misclassification cost is presented with missing values in test set after the cost-sensitive decision tree are constructed with missing values in training sets. Finally, the experimental results show our method outperform the existed methods in terms of the decrease of misclassification cost.}
    }