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We propose a new algorithm for clustering ensemble based on spectral clustering. We also propose a criteria along with this algorithm, for the detection of ...
Since a large number of clustering algorithms exist, aggregating different clustered partitions into a single consolidated one to obtain better results has ...
In this paper, we have proposed a new algorithm for clustering ensemble called Spectral Aggregation. This algorithm is based on the 0-1 affinity matrix for clus ...
Our algorithm can determine the number of clusters more accurately with less volatility, and therefore can deduce a better combined clustering result.
Our algorithm can determine the number of clusters more accurately with less volatility, and therefore can deduce a better combined clustering result.
Bibliographic details on Spectral aggregation for clustering ensemble.
Nov 20, 2023 · While ensemble clustering yields promising results on simple dataset, it has not been fully explored on complex multi-dimensional dataset.
We propose a robust and fuzzy ensemble framework via spectral learning for RP-FCM clustering. After using random projection to generate different dimensional ...
Mar 16, 2024 · We propose an effective multi-modal clustering model scEMC for parallel scRNA and Assay of Transposase Accessible Chromatin data.
Aug 10, 2015 · Ensemble clustering, also known as consensus clustering, is emerging as a promising solution for multi-source and/or heterogeneous data ...