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- W2965141107 abstract "Clustering is an unsupervised machine learning technique involving the grouping of data points used to classify objects or cases into related groups known as clusters. There are different clustering methods, each with its own advantages and disadvantages. Our main focus in this paper is the newly developed Convex clustering algorithm. Convex clustering uses some hierarchical clustering features while reducing the ability to make false inferences. However, convex clustering is computationally demanding and there are two main obstacles in its path: (a) it is poorly situated on high-dimensional problems and (b) minimal guidance on how to choose penalty weights. Our main objective is to attempt to modify the convex clustering algorithm in order to eliminate the above drawbacks." @default.
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- W2965141107 date "2019-08-01" @default.
- W2965141107 modified "2023-09-26" @default.
- W2965141107 title "Object Detection Using Convex Clustering – A Survey" @default.
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- W2965141107 doi "https://doi.org/10.1007/978-3-030-24643-3_117" @default.
- W2965141107 hasPublicationYear "2019" @default.
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