A hybrid unsupervised and supervised clustering applied to microarray data
نویسندگان
چکیده
منابع مشابه
Explanations of unsupervised learning clustering applied to data security analysis
Network security tests should be periodically conducted to detect vulnerabilities before they are exploited. However, analysis of testing results is resource intensive with many data and requires expertise because it is an unsupervised domain. This paper presents how to automate and improve this analysis through the identification and explanation of device groups with similar vulnerabilities. C...
متن کاملExplanations of unsupervised learning clustering applied to data security analysis
Network security tests should be periodically conducted to detect vulnerabilities before they are exploited. However, analysis of testing results is resource intensive with many data and requires expertise because it is an unsupervised domain. This paper presents how to automate and improve this analysis through the identification and explanation of device groups with similar vulnerabilities. C...
متن کاملHybrid Algorithm for Clustering of Microarray Data
Clustering is a crucial step in the analysis of gene expression data. Its goal is to identify the natural clusters and provide a reliable estimate of the number of distinct clusters in a given data set. In this paper we propose new hybrid algorithm for clustering of microarray data based on spectral clustering and k-means. Our algorithm consist of four steps, including preprocessing or filterin...
متن کاملExtracting Prior Knowledge from Data Distribution to Migrate from Blind to Semi-Supervised Clustering
Although many studies have been conducted to improve the clustering efficiency, most of the state-of-art schemes suffer from the lack of robustness and stability. This paper is aimed at proposing an efficient approach to elicit prior knowledge in terms of must-link and cannot-link from the estimated distribution of raw data in order to convert a blind clustering problem into a semi-supervised o...
متن کاملHybrid hierarchical clustering with applications to microarray data.
In this paper, we propose a hybrid clustering method that combines the strengths of bottom-up hierarchical clustering with that of top-down clustering. The first method is good at identifying small clusters but not large ones; the strengths are reversed for the second method. The hybrid method is built on the new idea of a mutual cluster: a group of points closer to each other than to any other...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems
سال: 2013
ISSN: 1805-5443
DOI: 10.11601/ijates.v2i3.21