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A Teacher-Cost-Sensitive Decision-Theoretic Rough Set Model

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Rough Sets and Knowledge Technology (RSKT 2015)

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Existing DTRS models use two states (success, fail) and three actions (accept, defer, reject) to describe the decision procedure. However, deferment provides a compromise instead of a solution. In this paper, we replace this action with consult which stands for consulting a teacher for correct classification. Naturally, the new action involves the cost of teacher, which is already known in many applications. Through computing the thresholds \(\alpha \) and \(\beta \) with the misclassification cost and the teacher cost from the decision system, the positive, the boundary, and the negative regions are obtained. They correspond to positive rules for acceptance, boundary rules for consulting a teacher, and negative rules for rejection, respectively. We compare the new model with the Pawlak model and previous DTRS model through an example. This study indicates a new research direction of DTRS.

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This work is in part supported by National Science Foundation of China under Grant No. 61379089.

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Correspondence to Fan Min .

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He, YW., Zhang, HR., Min, F. (2015). A Teacher-Cost-Sensitive Decision-Theoretic Rough Set Model. In: Ciucci, D., Wang, G., Mitra, S., Wu, WZ. (eds) Rough Sets and Knowledge Technology. RSKT 2015. Lecture Notes in Computer Science(), vol 9436. Springer, Cham.

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  • Print ISBN: 978-3-319-25753-2

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