کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533964 870196 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic discriminant functions with missing feature values
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Dynamic discriminant functions with missing feature values
چکیده انگلیسی


• Datasets with missing feature values are common, especially in biometric datasets.
• An enhanced Fisher’s discriminant that supports missing features is proposed.
• A modified regularization method is derived.
• The new framework is evaluated on 4 image datasets and 4 fingerprint datasets.
• Significant reduction of errors is achieved, compared with traditional techniques.

Datasets with missing feature values are often encountered, especially in biometric databases. A common solution is to fill in the missing values by imputation. Unfortunately there is no universally best imputation method and the performance of a classifier can be degraded by poor imputations. In this paper, we propose a framework called the dynamic Fisher’s linear discriminant that uses a quadratic classifier with a dynamically modified quadratic discriminant function. By eliminating imputations as far as possible, the proposed framework is useful for pattern classification. Satisfactory results are obtained from experiments conducted on four datasets from the UCI machine learning repository and the KEEL dataset repository, together with four fingerprint datasets.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 34, Issue 13, 1 October 2013, Pages 1548–1556
نویسندگان
, ,