Feature weight estimation for gene selection: a local hyperlinear learning approach
نویسندگان
چکیده
منابع مشابه
A Common Weight Data Envelopment Analysis Approach for Material Selection
Material selection is one of the major problems in manufacturing environments since the improper selected material may lead to fail in the production processes and result in customer dissatisfaction and cost inefficiency. Every material has different properties which should be considered as major criteria during the material selection procedure. Selection criteria could be quantitative or quali...
متن کاملImprovement of effort estimation accuracy in software projects using a feature selection approach
In recent years, utilization of feature selection techniques has become an essential requirement for processing and model construction in different scientific areas. In the field of software project effort estimation, the need to apply dimensionality reduction and feature selection methods has become an inevitable demand. The high volumes of data, costs, and time necessary for gathering data , ...
متن کاملA Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization
Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...
متن کاملA Model Selection Approach for Local Learning
Local learning techniques, for each query, extract a prediction interpolating locally the neighboring examples which are considered relevant according to a distance measure. As other learning approaches, the local learning procedure can be conveniently decomposed into a parametric identification and a structural identification. While parametric identification is reduced to a linear regression, ...
متن کاملFeature 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 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: BMC Bioinformatics
سال: 2014
ISSN: 1471-2105
DOI: 10.1186/1471-2105-15-70