Report
Can FCA-based Recommender System Suggest a Proper Classifier?
| 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 |
| الوصف غير متاح. |