Mar 27, 2020 · We present the new clustering algorithm MAPK-means (Metric Attribute Preferential K-means) that minimizes our clustering objective function.
It uses a preference vector, which is the expected feature weight. Besides, a confidence level is introduced to enable users to express their confidence to ...
Jan 1, 2020 · This paper describes a new semi-supervised clustering algorithm as part of a more general framework of interactive exploratory clustering.
This paper argues that initial feature weights and cluster centers are equally important in determining the final partition and suggests using feature level ...
MAPK-means: A clustering algorithm with quantitative preferences on attributes. https://doi.org/10.3233/ida-184468 ·. Journal: Intelligent Data Analysis, 2020 ...
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This paper proposes a new semi-supervised clustering framework to represent and integrate quantitative preferences on attributes. A new metric learning ...
Jul 1, 2024 · MAPK-means: A clustering algorithm with quantitative preferences on attributes. Adnan El Moussawi , Arnaud Giacometti , Nicolas Labroche ...
This paper proposes a new semi-supervised clustering framework to represent and integrate quantitative preferences on attributes.
... This paper extends the work presented in [29] that introduced a first version of the algorithm MAPK-means. Compared to this first version, the ...
The mitogen-activated protein kinases (MAPKs) regulate diverse cellular programs by relaying extracellular signals to intracellular responses.