Modifying the feature-selective validation method to validate noisy data sets
نویسندگان
چکیده
منابع مشابه
A method to solve the problem of missing data, outlier data and noisy data in order to improve the performance of human and information interaction
Abstract Purpose: Errors in data collection and failure to pay attention to data that are noisy in the collection process for any reason cause problems in data-based analysis and, as a result, wrong decision-making. Therefore, solving the problem of missing or noisy data before processing and analysis is of vital importance in analytical systems. The purpose of this paper is to provide a metho...
متن کاملStudy of Transient Phenomena with Feature Selective Validation Method
In recent years, computational electromagnetism has had a great development thanks to the computational systems speed increase and their cost reduction. With those improvements the mathematical algorithms are able to work properly with more practical EMC issues. The problem that arises many times is to become confident with the results, in other words, to be able to quantitatively validate the ...
متن کاملFeature Curve Co-Completion in Noisy Data
Feature curves on 3D shapes provide important hints about significant parts of the geometry and reveal their underlying structure. However, when we process real world data, automatically detected feature curves are affected by measurement uncertainty, missing data, and sampling resolution, leading to noisy, fragmented, and incomplete feature curve networks. These artifacts make further processi...
متن کاملFeature Selection for Small Sample Sets with High Dimensional Data Using Heuristic Hybrid Approach
Feature selection can significantly be decisive when analyzing high dimensional data, especially with a small number of samples. Feature extraction methods do not have decent performance in these conditions. With small sample sets and high dimensional data, exploring a large search space and learning from insufficient samples becomes extremely hard. As a result, neural networks and clustering a...
متن کاملA hybrid filter-based feature selection method via hesitant fuzzy and rough sets concepts
High dimensional microarray datasets are difficult to classify since they have many features with small number ofinstances and imbalanced distribution of classes. This paper proposes a filter-based feature selection method to improvethe classification performance of microarray datasets by selecting the significant features. Combining the concepts ofrough sets, weighted rough set, fuzzy rough se...
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: IET Science, Measurement & Technology
سال: 2008
ISSN: 1751-8822,1751-8830
DOI: 10.1049/iet-smt:20070063