• Publications
  • Influence
Fuzzy-rough nearest neighbor algorithms in classification
  • M. Sarkar
  • Computer Science, Mathematics
  • Fuzzy Sets Syst.
  • 1 October 2007
In this paper, classification efficiency of the conventional K-nearest neighbor algorithm is enhanced by exploiting fuzzy-rough uncertainty. The simplicity and nonparametric characteristics of theExpand
  • 95
  • 9
Fuzzy-rough nearest neighbors algorithm
  • M. Sarkar
  • Computer Science
  • Smc conference proceedings. ieee international…
  • 8 October 2000
In this paper the classification efficiency of the conventional K-nearest neighbors algorithm is enhanced by exploiting the fuzzy-rough uncertainty. The simplicity and nonparametric characteristicsExpand
  • 35
  • 6
A clustering algorithm using an evolutionary programming-based approach
In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm effectively groups a given set of data into an optimum number of clusters. The proposed method isExpand
  • 112
  • 3
Characterization of medical time series using fuzzy similarity-based fractal dimensions
This paper attempts to characterize medical time series using fractal dimensions. Existing fractal dimensions like box, information and correlation dimensions characterize the time series byExpand
  • 25
  • 3
Modular pattern classifiers: a brief survey
  • M. Sarkar
  • Computer Science
  • Smc conference proceedings. ieee international…
  • 8 October 2000
While solving a complex pattern classification problem, it is often difficult to design a monolithic classifier. One approach is to divide the problem into smaller ones, and solve each subproblemExpand
  • 15
  • 3
Rough-fuzzy functions in classification
  • M. Sarkar
  • Computer Science, Mathematics
  • Fuzzy Sets Syst.
  • 16 December 2002
This paper generalizes the concept of rough membership functions in pattern classification tasks to rough-fuzzy membership functions and rough-fuzzy ownership functions. Unlike the rough membershipExpand
  • 68
  • 1
Application of K-nearest neighbors algorithm on breast cancer diagnosis problem
This paper addresses the Breast Cancer diagnosis problem as a pattern classification problem. Specifically, this problem is studied using the Wisconsin-Madison Breast Cancer data set. The K-nearestExpand
  • 67
  • 1
Fuzzy K-means clustering with missing values
Fuzzy K-means clustering algorithm is a popular approach for exploring the structure of a set of patterns, especially when the clusters are overlapping or fuzzy. However, the fuzzy K-means clusteringExpand
  • 41
  • 1
Feedforward neural networks configuration using evolutionary programming
This paper proposes an evolutionary programming based neural network construction algorithm, that efficiently configures feedforward neural networks in terms of optimum structure and optimumExpand
  • 19
  • 1
Rough-fuzzy membership functions
This paper generalizes the concept of rough membership functions in pattern classification tasks to rough-fuzzy membership functions. Unlike the rough membership value of a pattern, which isExpand
  • 20
  • 1