Open AccessJournal Article10.1016/J.FSS.2008.03.019

Adaptive prototype-based fuzzy classification

- 01 Nov 2008

- Vol. 159, Iss: 21, pp 2806-2818

TL;DR: This work proposes a new adaptive active clustering scheme, based on an initial fuzzy c-means clustering and learning vector quantization, which can initially cluster large datasets unsupervised and then allows for adjustment of the classification by the user.

About: This article is published in Fuzzy Sets and Systems. The article was published on 01 Nov 2008. and is currently open access. The article focuses on the topics: Fuzzy clustering & Fuzzy classification.

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In this work, the authors explore the problem of classifying hundreds of thousands of cell assay images obtained by a high-throughput screening camera.. The authors propose a new adaptive active clustering scheme, based on an initial fuzzy c-means clustering and learning vector quantization.. A framework for the classification of cell assay images based on this technique is introduced.. The authors compare their approach to other related techniques in this field based on several datasets.

Fig. 4. Two clusters that overlap and the resulting area of possible confusion.

Fig. 10. Active SVM on pap-smear dataset.

Fig. 9. Active LVQ on pap-smear dataset.

Fig. 1. Original cell image taken by a high-throughput screening microscope camera.

Fig. 8. Single Sampling vs. Batch Sampling.

Citations

The Self-Organizing Map

Teuvo Kohonen

- 01 Jan 1990

TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.

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Instance-based classifiers applied to medical databases: Diagnosis and knowledge extraction

Francesco Gagliardi

- 01 Jul 2011

- Artificial Intelligence in Medicine

TL;DR: This study shows that IB methods - most notably, the optimized k-NNC and the PEL-C - can be used and may be advantageous for clinical decision support systems and that IB classifiers can be use for nosological knowledge extraction.

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Fuzzy Clustering Based Image Segmentation of Pap smear Images of Cervical Cancer Cell Using FCM Algorithm

Jyotismita Talukdar

- 01 Jan 2013

TL;DR: In this study, three validity measures are used; partition coefficient (PC), partition entropy (PE), and compactness and separation function (SC), which measures the goodness of the clustering result.

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Optimal Information-based Classification.

Baro Hyun

- 01 Jan 2011

TL;DR: This dissertation touches upon several topics that relate to the problem of classification, such as information, classification, and team classification, for classifiers that follow two models: classifiers with workload-independent and workload-dependent performance.

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Journal Article•10.1016/j.asoc.2023.110917

Fuzzy classification with distance-based depth prototypes: High-dimensional unsupervised and/or supervised problems

I. Irigoien, +3 more

- 01 Nov 2023

- Applied Soft Computing

TL;DR: This paper proposes a fuzzy supervised classification method using distance-based depth prototypes, applicable to high-dimensional data and unsupervised classification, outperforming existing methods on synthetic and real-world biomedical and industrial datasets.

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References

Journal Article•10.1126/SCIENCE.220.4598.671

Optimization by Simulated Annealing

Scott Kirkpatrick, +2 more

- 13 May 1983

- Science

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.

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Journal Article•10.1109/TSMC.1973.4309314

Textural Features for Image Classification

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TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.

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•Book

Pattern Recognition with Fuzzy Objective Function Algorithms

James C. Bezdek

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TL;DR: Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.

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UCI Repository of machine learning databases

Catherine Blake

- 01 Jan 1998

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Journal Article•10.1109/5.58325

The self-organizing map

Teuvo Kohonen

- 01 Sep 1990

TL;DR: The self-organizing map, an architecture suggested for artificial neural networks, is explained by presenting simulation experiments and practical applications, and an algorithm which order responses spatially is reviewed, focusing on best matching cell selection and adaptation of the weight vectors.

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9.9K

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Adaptive prototype-based fuzzy classification

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1. What are the contributions mentioned in the paper "Adaptive prototype-based fuzzy classification" ?

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Citations

The Self-Organizing Map

Instance-based classifiers applied to medical databases: Diagnosis and knowledge extraction

Fuzzy Clustering Based Image Segmentation of Pap smear Images of Cervical Cancer Cell Using FCM Algorithm

Optimal Information-based Classification.

Fuzzy classification with distance-based depth prototypes: High-dimensional unsupervised and/or supervised problems

References

Optimization by Simulated Annealing

Textural Features for Image Classification

Pattern Recognition with Fuzzy Objective Function Algorithms

UCI Repository of machine learning databases

The self-organizing map

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