نتایج جستجو برای: supervised clustering

تعداد نتایج: 137572  

Journal: :MATEC Web of Conferences 2017

2005
Christoph F. Eick Nidal M. Zeidat

This paper centers on a novel data mining technique we term supervised clustering. Unlike traditional clustering, supervised clustering is applied to classified examples and has the goal of identifying class-uniform clusters that have a high probability density. This paper focuses on how data mining techniques in general, and classification techniques in particular, can benefit from knowledge o...

Journal: :International Journal of Artificial Intelligence & Applications 2012

Journal: :Procedia Computer Science 2019

Journal: :International Journal of Approximate Reasoning 2021

Semi-supervised clustering is a constrained technique that organizes collection of unlabeled data into homogeneous subgroups with the help domain knowledge expressed as constraints. These methods are, most time, variants popular k-means algorithm. As such, they are based on criterion to minimize. Amongst existing semi-supervised clusterings, Evidential Clustering (SECM) deals problem uncertain/...

2015
Keun-Chang Kwak

In this paper, a cluster validity concept from an unsupervised to a supervised manner is presented. Most cluster validity criterions were established in an unsupervised manner, although many clustering methods performed in supervised and semi-supervised environments that used context information and performance results of the model. Context-based clustering methods can divide the input spaces u...

Journal: :IEEE transactions on image processing 2021

Auto-Encoder (AE)-based deep subspace clustering (DSC) methods have achieved impressive performance due to the powerful representation extracted using neural networks while prioritizing categorical separability. However, self-reconstruction loss of an AE ignores rich useful relation information and might lead indiscriminative representation, which inevitably degrades performance. It is also cha...

2013
Kai Li Yufei Zhou

Semi-supervised clustering is an important method which can improve clustering performance by introducing partial supervised information. This paper mainly studies the semi-supervised fuzzy clustering based on Mahalanobis distance and Gaussian Kernel for SCAPC algorithm. Here, we give a new semi-supervised fuzzy clustering objective function. By solving the optimization problem with above objec...

2006
Nidal Zeidat Christoph F. Eick Zhenghong Zhao

This work centers on a novel data mining technique we term supervised clustering. Unlike traditional clustering, supervised clustering assumes that the examples are classified and has the goal of identifying class-uniform clusters that have high probability densities. Three representative–based algorithms for supervised clustering are introduced: two greedy algorithms SRIDHCR and SPAM, and an e...

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