Feature Subset Selection for Cancer Classification Using Weight Local Modularity
نویسندگان
چکیده
منابع مشابه
Feature Subset Selection for Cancer Classification Using Weight Local Modularity
Microarray is recently becoming an important tool for profiling the global gene expression patterns of tissues. Gene selection is a popular technology for cancer classification that aims to identify a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers to obtain a high predictive accuracy. This technique has been extensively studied in rece...
متن کاملImage Classification Using Feature Subset Selection
Classification technology is essential for fast retrieval in large database. This paper proposes a combining GA and SVM model to content-based image retrieval. The proposed method is also used to classification similar images from database. Joint HSV histogram and average entropy computed from gray-level co-occurrence matrices in the localized image region is employed as input vectors. Genetic ...
متن کاملAn optimal feature subset selection using GA for leaf classification
This paper describes an optimal approach for feature extraction and selection for classification of leaves based on Genetic Algorithm (GA). The selection of the optimal features subset and the classification has become an important methodology in the field of Leaf classification. The deterministic feature sequence is extracted from the leaf images using GA technique, and these extracted feature...
متن کاملA New Hybrid Feature Subset Selection Algorithm for the Analysis of Ovarian Cancer Data Using Laser Mass Spectrum
Introduction: Amajor problem in the treatment of cancer is the lack of an appropriate method for the early diagnosis of the disease. The chemical reaction within an organ may be reflected in the form of proteomic patterns in the serum, sputum, or urine. Laser mass spectrometry is a valuable tool for extracting the proteomic patterns from biological samples. A major challenge in extracting such ...
متن کاملFeature Subset Selection and Classification Using Hybrid Improved Svm
Many feature subset selection algorithms have been proposed, but not all of them are appropriate for a given feature selection problem. At the same time, so far there is rarely a good way to choose appropriate feature subset selection algorithms for the problem at hand. Feature selection has become an essential element in the Data Mining process. In this paper, investigate the problem of effici...
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: Scientific Reports
سال: 2016
ISSN: 2045-2322
DOI: 10.1038/srep34759