Keyword: Fuzzy K-Means : Search

More Web Proxy on the site http://driver.im/

Applied Filters

Publications

Conferences

Publication Date

4 Results for: Keyword: Fuzzy K-MeansEdit SearchSave SearchRSS

Searched The ACM Guide to Computing Literature (3,801,463 records)|Limit your search to The ACM Full-Text Collection (771,159 records)

Showing 1 - 4of4 Results

Select All

Export Citations Save to Binder

per page:

Recency

Article
August 2024
Unsupervised Feature Selection via Fuzzy K-Means and Sparse Projection
Web and Big DataPages 224–239https://doi.org/10.1007/978-981-97-7244-5_15
Abstract
Recent years, unsupervised feature selection (UFS) has obtained widespread attention in various tasks of high-dimensional data mining. However, how to characterize the potential structural information of unlabeled data samples remains an ... $_{}$
0
Metrics
Total Citations0
article
January 2018
Proficient Normalised Fuzzy K-Means With Initial Centroids Methodology
International Journal of Knowledge Discovery in Bioinformatics (IJKDB), Volume 8, Issue 1Pages 42–59https://doi.org/10.4018/IJKDB.2018010104

This article describes how data is relevant and if it can be organized, linked with other data and grouped into a cluster. Clustering is the process of organizing a given set of objects into a set of disjoint groups called clusters. There are a number ...
0
Metrics
Total Citations0
Article
April 2009
Texture Segmentation Based on Probabilistic Index Maps
ICETC '09: Proceedings of the 2009 International Conference on Education Technology and ComputerPages 35–39https://doi.org/10.1109/ICETC.2009.41

The Probabilistic Index Map (PIM) model was originally proposed for video processing to extract background of video frames. In this paper, we introduce the PIM model for texture segmentation. We first extract texture features based on Laws and Gabor ...
0
Metrics
Total Citations0
Article
March 2009
A Novel Text Clustering Method Based on TGSOM and Fuzzy K-Means
ETCS '09: Proceedings of the 2009 First International Workshop on Education Technology and Computer Science - Volume 01Pages 26–30https://doi.org/10.1109/ETCS.2009.14

According to the high-dimensional sparse features of the storage of the textual document, and defects existing in the clustering methods which havealready studied by now and some other problems, an effective text clustering approach (short for TGSOM-FS-...
0
Metrics
Total Citations0