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pro vyhledávání: '"Swagatam Das"'
On the unification of possibilistic fuzzy clustering: Axiomatic development and convergence analysis
Autor:
Swagatam Das, Arkajyoti Saha
Publikováno v:
Fuzzy Sets and Systems. 340:73-90
Fuzzy partitional clustering algorithms like Fuzzy C-means (FCM) are sensitive to noise points or outliers because of the probabilistic constraint (the sum of the membership values of a specific data point to all the clusters is 1), which enables it
Autor:
Ayan Das, Swagatam Das
Publikováno v:
Pattern Recognition Letters. 88:12-19
Presents a simultaneous feature weighting and selection method.Uses non-linear information measure with L1 penalty to form the objective function.Experimentally determines the best constraint on weight vectors.Uses MOEA/D to solve the bi-objective op
Publikováno v:
Pattern Recognition Letters. 80:231-237
kNN-FWPD classifier is proposed with FWPD as the underlying dissimilarity measure.kNN-FWPD classifier can be directly applied to datasets having missing features.The proposed classifier has similar time complexity compared to the kNN classifier.Exper
Simultaneous feature selection and weighting – An evolutionary multi-objective optimization approach
Autor:
Swagatam Das, Sujoy Paul
Publikováno v:
Pattern Recognition Letters. 65:51-59
Selection of feature subset is a preprocessing step in computational learning, and it serves several purposes like reducing the dimensionality of a dataset, decreasing the computational time required for classification and enhancing the classificatio
Autor:
Swagatam Das, Arkajyoti Saha
Publikováno v:
Neurocomputing. 166:422-435
This article presents and investigates a new variant of the fuzzy k-Modes clustering algorithm for categorical data with automated feature weight learning. The modification strengthens the classical fuzzy k-Modes algorithm by associating higher weigh
Publikováno v:
Statistics & Probability Letters. 163:108781
Optimal Transport (OT) distances result in a powerful technique to compare the probability distributions. Defining a similarity measure between clusters has been an open problem in Statistics. This paper introduces a hierarchical clustering algorithm
Fuzzy clustering methods identify naturally occurring clusters in a dataset, where the extent to which different clusters are overlapped can differ. Most methods have a parameter to fix the level of fuzziness. However, the appropriate level of fuzzin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ffdef2024d5e8df3430d841db0d4892
http://arxiv.org/abs/1808.03327
http://arxiv.org/abs/1808.03327
Autor:
Swagatam Das, Tribeni Prasad Banerjee
Publikováno v:
Information Sciences. 217:96-107
Motor fault diagnosis in dynamic condition is a typical multi-sensor data fusion problem. It involves the use of information collected from multiple sensors, such as vibration, sound, current, voltage, and temperature, to detect and identify motor fa
This book and its companion volumes, LNCS volumes 9140, 9141 and 9142, constitute the proceedings of the 6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the Second BRICS Congress on Computational Intelligence, C
This book and its companion volumes, LNCS volumes 9140, 9141 and 9142, constitute the proceedings of the 6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the Second BRICS Congress on Computational Intelligence, C