Aufgrund von Vorbereitungen auf eine neue Version von KOPS, können kommenden Montag und Dienstag keine Publikationen eingereicht werden. (Due to preparations for a new version of KOPS, no publications can be submitted next Monday and Tuesday.)
Type of Publication: | Journal article |
URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-opus-70549 |
Author: | Cebron, Nicolas; Berthold, Michael R. |
Year of publication: | 2005 |
Published in: | ICDM ; 2005. - pp. 63-69 |
Summary: |
Classifying large datasets without any a-priori information poses a problem especially in the field of bioinformatics. In this work, we explore the problem of classifying hundreds of thousands of cell assay images obtained by a highthroughput screening camera. The goal is to label a few selected examples by hand and to automatically label the rest of the images afterwards. We deal with three major requirements: first, the model should be easy to understand, second it should offer the possibility to be adjusted by a domain expert, and third the interaction with the user should be kept to a minimum. We propose a new active clustering scheme, based on an initial Fuzzy c-means clustering and Learning Vector Quantization. This scheme can initially cluster large datasets unsupervised and then allows for adjustment of the classification by the user. Furthermore, we introduce a framework for the classification of cell assay images based on this technique. Early experiments show promising results.
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Subject (DDC): | 004 Computer Science |
Link to License: | Attribution-NonCommercial-NoDerivs 2.0 Generic |
Bibliography of Konstanz: | Yes |
CEBRON, Nicolas, Michael R. BERTHOLD, 2005. Mining of Cell Assay Images Using Active Semi-Supervised-Clustering. In: ICDM, pp. 63-69
@article{Cebron2005Minin-5769, title={Mining of Cell Assay Images Using Active Semi-Supervised-Clustering}, year={2005}, journal={ICDM}, pages={63--69}, author={Cebron, Nicolas and Berthold, Michael R.} }
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