The identification of influential subsets in regression using a fuzzy clustering strategy

Fuzzy K-Means clustering (FKM) is one of the most popular methods to partition data into clusters. Traditional FKM and its extensions perform fuzzy clustering based on original high-dimensional features. However, the presence of noisy and ...

Crisp and fuzzy clustering methods based on a combination of univariate and multivariate wavelet features are considered for the clustering of multivariate time series. The performance of each of these methods is evaluated for stationary and variance ...

In this paper the conventional fuzzy k-modes algorithm for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. Use of fuzzy ...