Results 31 to 40 of about 6,969,735 (365)
Dynamic Feature Selection for Clustering High Dimensional Data Streams
IEEE Access, 2019 Change in a data stream can occur at the concept level and at the feature level. Change at the feature level can occur if new, additional features appear in the stream or if the importance and relevance of a feature changes as the stream progresses. This
Conor Fahy, Shengxiang Yang
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Utility metric for unsupervised feature selection [PDF]
PeerJ Computer Science, 2021 Feature selection techniques are very useful approaches for dimensionality reduction in data analysis. They provide interpretable results by reducing the dimensions of the data to a subset of the original set of features.
Amalia Villa +4 more
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A review of feature selection techniques in bioinformatics
Bioinform., 2007 Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in ...
Yvan Saeys +2 more
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Applied Computational Intelligence and Soft Computing, 2021 Heart disease is recognized as one of the leading factors of death rate worldwide. Biomedical instruments and various systems in hospitals have massive quantities of clinical data.
Kaushalya Dissanayake, M. Johar
semanticscholar +1 more source
New Feature Selection Algorithm Based on Feature Stability and Correlation
IEEE Access, 2022 The analysis of a large amount of data with high dimensionality of rows and columns increases the load of machine learning algorithms. Such data are likely to have noise and consequently, obstruct the performance of machine learning algorithms.
Luai Al-Shalabi
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Online Feature Selection for Visual Tracking [PDF]
, 2016 Object tracking is one of the most important tasks in many applications of computer vision. Many tracking methods use a fixed set of features ignoring that appearance of a target object may change drastically due to intrinsic and extrinsic factors.
Melzi, Simone, Roffo, Giorgio
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Supervised Feature Selection With a Stratified Feature Weighting Method
IEEE Access, 2018 Feature selection has been a powerful tool to handle high-dimensional data. Most of these methods are biased toward the highest rank features which may be highly correlated with each other.
Renjie Chen +4 more
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Feature extraction for epileptic seizure detection using machine learning
Current Medicine Research and Practice, 2020 Background: Epilepsy is a common neurological disorder and affects approximately 70 million people worldwide. The traditional approach used by neurologists for the detection of seizure is time consuming.
Renuka Mohan Khati, Rajesh Ingle
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Procedia Computer Science, 2016 AbstractFeature selection, as a dimensionality reduction technique, aims to choosing a small subset of the relevant features from the original features by removing irrelevant, redundant or noisy features. Feature selection usually can lead to better learning performance, i.e., higher learning accuracy, lower computational cost, and better model ...
Lingfeng Niu, Jianyu Miao
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Quadratic Mutual Information Feature Selection
Entropy, 2017 We propose a novel feature selection method based on quadratic mutual information which has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct estimation of quadratic mutual information from data samples using Gaussian ...
Davor Sluga, Uroš Lotrič
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