Can FCA-based Recommender System Suggest a Proper Classifier?

التفاصيل البيبلوغرافية
العنوان: Can FCA-based Recommender System Suggest a Proper Classifier?
المؤلفون: Kashnitsky, Yury, Ignatov, Dmitry I.
المصدر: CEUR Workshop Proceedings, 1257, pp. 17-26 (2014)
سنة النشر: 2015
المجموعة: Computer Science
Statistics
مصطلحات موضوعية: Computer Science - Information Retrieval, Computer Science - Learning, Statistics - Machine Learning
الوصف: The paper briefly introduces multiple classifier systems and describes a new algorithm, which improves classification accuracy by means of recommendation of a proper algorithm to an object classification. This recommendation is done assuming that a classifier is likely to predict the label of the object correctly if it has correctly classified its neighbors. The process of assigning a classifier to each object is based on Formal Concept Analysis. We explain the idea of the algorithm with a toy example and describe our first experiments with real-world datasets.
Comment: 10 pages, 1 figure, 4 tables, ECAI 2014, workshop "What FCA can do for "Artifficial Intelligence"
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/1504.05473
رقم الانضمام: edsarx.1504.05473
قاعدة البيانات: arXiv
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