頁籤選單縮合
題 名 | Forecasting Credit Ratings by the Pairwise Classifier |
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作 者 | Hwang, Ruey-Ching; | 書刊名 | 中國統計學報 |
卷 期 | 45:2 2007.06[民96.06] |
頁 次 | 頁144-169 |
分類號 | 319.5 |
關鍵詞 | Industry effect; Market-driven variable; Ordered probit model; Pairwise classifier; Standard and poor's ratings; |
語 文 | 英文(English) |
英文摘要 | Multiclass classification models are important to the prediction of credit ratings. In this paper, we propose a pairwise classifier to predict credit ratings. Our basic approach is to first convert the multiclass classification problem into multiple two-class classification problems, and then the final prediction rule is obtained by aggregating the results from multiple two-class predictions. We present some empirical results to show that such pairwise classifier significantly improves the prediction accuracy rates from 65% to 75%. |
本系統中英文摘要資訊取自各篇刊載內容。