نتایج جستجو برای: feature subset selection
تعداد نتایج: 614385 فیلتر نتایج به سال:
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 ...
pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. the surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (seldi-tof ms) has been used to generate proteomic profiles from biological fluids. mass spectrometry yields redundant noisy data that the most data points are irrelevant features ...
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 , ...
Hyper spectral remote sensing imagery, due to its rich source of spectral information provides an efficient tool for ground classifications in complex geographical areas with similar classes. Referring to robustness of Support Vector Machines (SVMs) in high dimensional space, they are efficient tool for classification of hyper spectral imagery. However, there are two optimization issues which s...
Feature Selection (FS) is an important pre-processing step in machine learning and data mining. All the traditional feature selection methods assume that the entire feature space is available from the beginning. However, online streaming features (OSF) are an integral part of many real-world applications. In OSF, the number of training examples is fixed while the number of features grows with t...
Increasing the use of Internet and some phenomena such as sensor networks has led to an unnecessary increasing the volume of information. Though it has many benefits, it causes problems such as storage space requirements and better processors, as well as data refinement to remove unnecessary data. Data reduction methods provide ways to select useful data from a large amount of duplicate, incomp...
Feature subset selection has become more and more a common topic of research. This popularity is partly due to the growth in the number of features and application domains. It is of the greatest importance to take the most of every evaluation of the inducer, which is normally the more costly part. In this paper, a technique is proposed that takes into account the inducer evaluation both in the ...
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