A New Approach to Fuzzy-Rough Nearest Neighbour Classification
نویسندگان
چکیده
In this paper, we present a new fuzzy-rough nearest neighbour (FRNN) classification algorithm, as an alternative to Sarkar’s fuzzyrough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the experimental analysis, we evaluate our approach with both classical fuzzy-rough approximations (based on an implicator and a t-norm), as well as with the recently introduced vaguely quantified rough sets. Preliminary results are very good, and in general FRNN outperforms both FRNN-O, as well as the traditional fuzzy nearest neighbour (FNN) algorithm.
منابع مشابه
Fuzzy-Rough Nearest Neighbour Classification
A new fuzzy-rough nearest neighbour (FRNN) classification algorithm is presented in this paper, as an alternative to Sarkar’s fuzzyrough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and upper approximations of decision classes, and classifies test instances based on their membership to these approximations. In the exp...
متن کاملKernel-Based Fuzzy-Rough Nearest Neighbour Classification.dvi
Fuzzy-rough sets play an important role in dealing with imprecision and uncertainty for discrete and real-valued or noisy data. However, there are some problems associated with the approach from both theoretical and practical viewpoints. These problems have motivated the hybridisation of fuzzy-rough sets with kernel methods. Existing work which hybridises fuzzy-rough sets and kernel methods emp...
متن کاملFuzzy-rough nearest neighbour classification and prediction
In this paper, we propose a nearest neighbour algorithm that uses the lower and upper approximations from fuzzy rough set theory in order to classify test objects, or predict their decision value. It is shown experimentally that our method outperforms other nearest neighbour approaches (classical, fuzzy and fuzzy-rough ones) and that it is competitive with leading classification and prediction ...
متن کاملHesitant Fuzzy k-Nearest Neighbour (HFK-NN) Classifier for Document Classification and Numerical Result Analysis
This paper presents new approach Hesitant Fuzzy K-nearest neighbour (HFK-nn) based document classification and numerical results analysis. The proposed classification Hesitant Fuzzy K-nearest neighbour (HFKnn) approach is based on hesitant Fuzzy distance. In this paper we have used hesitant Fuzzy distance calculations for document classification results. The following steps are used for classif...
متن کاملFuzzy-Rough Nearest-Neighbor Classification Approach
This paper proposes a new --rough nearest-neighbor (NN ) approach based on the fuzzy-rough sets theory. This approach is more suitable to be used under partially exposed and unbalanced data set compared with crisp NN and fuzzy NN approach. Then the new method is applied to China listed company financial distress prediction, a typical classification task under partially exposed and unbalanced le...
متن کامل