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This paper deals with the task of finding a set of prototypes from the training set. A reduced set is obtained which is used instead of the training set when nearest neighbour classification is used. Prototypes are added in an incremental fashion, where at each step of the algorithm, the number of prototypes selected keeps on increasing. The number of patterns in the training data classified correctly also keeps on increasing till all patterns are classified properly. After this, a deletion operator is used where some prototypes which are not so useful are removed. This method has been used to obtain the prototypes for a variety of benchmark data sets and results have been presented
The k-nearest neighbour rule is commonly considered for classification tasks given its straightforwa...
k-Nearest Neighbors is surely one of the most important and widely adopted non-parametric classifica...
Most of the prototype reduction schemes (PRS), which have been reported in the literature, process t...
This paper deals with the task of finding a set of prototypes from the training set. A reduced set i...
Abstract—The nearest neighbor (NN) rule is one of the most successfully used techniques to resolve c...
Prototype generation techniques have arisen as very competitive methods for enhancing the nearest ne...
The main two drawbacks of nearest neighbor based classifiers are: high CPU costs when the number of ...
Most of the Prototype Reduction Schemes (PRS), which have been reported in the literature, process t...
The problem addressed in this paper concerns the prototype reduction for a nearest-neighbor classifi...
based on nearest neighbor error minimization ∗ A prototype reduction algorithm is proposed which sim...
Abstract—The nearest neighbor classifier is one of the most used and well-known techniques for perfo...
Prototype selection is a research field which has been active for more than four decades. As a resul...
There are two phases in pattern classi viz design phase (abstractions are created/learnt), classi p...
Abstract. Data reduction techniques improve the efficiency of k-Nearest Neigh-bour classification on...
Abstract Prototype Selection (PS), i.e., search for relevant subsets of instances, is an interesting...
The k-nearest neighbour rule is commonly considered for classification tasks given its straightforwa...
k-Nearest Neighbors is surely one of the most important and widely adopted non-parametric classifica...
Most of the prototype reduction schemes (PRS), which have been reported in the literature, process t...
This paper deals with the task of finding a set of prototypes from the training set. A reduced set i...
Abstract—The nearest neighbor (NN) rule is one of the most successfully used techniques to resolve c...
Prototype generation techniques have arisen as very competitive methods for enhancing the nearest ne...
The main two drawbacks of nearest neighbor based classifiers are: high CPU costs when the number of ...
Most of the Prototype Reduction Schemes (PRS), which have been reported in the literature, process t...
The problem addressed in this paper concerns the prototype reduction for a nearest-neighbor classifi...
based on nearest neighbor error minimization ∗ A prototype reduction algorithm is proposed which sim...
Abstract—The nearest neighbor classifier is one of the most used and well-known techniques for perfo...
Prototype selection is a research field which has been active for more than four decades. As a resul...
There are two phases in pattern classi viz design phase (abstractions are created/learnt), classi p...
Abstract. Data reduction techniques improve the efficiency of k-Nearest Neigh-bour classification on...
Abstract Prototype Selection (PS), i.e., search for relevant subsets of instances, is an interesting...
The k-nearest neighbour rule is commonly considered for classification tasks given its straightforwa...
k-Nearest Neighbors is surely one of the most important and widely adopted non-parametric classifica...
Most of the prototype reduction schemes (PRS), which have been reported in the literature, process t...
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