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Published in 2020 at "Journal of Chemometrics"
DOI: 10.1002/cem.3311
Abstract: Many real problems have been solved by support vector regression, especially v‐support vector regression (v‐SVR), but there are hyperparameters that usually needed to tune. In addition, v‐SVR cannot perform feature selection. Nature‐inspired algorithms have been…
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Keywords:
vector regression;
feature;
feature selection;
support vector ... See more keywords
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Published in 2022 at "International journal for numerical methods in biomedical engineering"
DOI: 10.1002/cnm.3599
Abstract: Hepatocellular carcinoma (HCC) is one of the major challenges facing biomedical research. Despite the high lethality, methods to predict mortality for this type of aggressive malignant tumor are insufficient. Machine learning is recognized by many…
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Keywords:
hepatocellular carcinoma;
feature selection;
algorithm;
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Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22823
Abstract: Common spatial pattern (CSP) is a widely adopted method for electroencephalogram (EEG) feature extraction in brain‐computer interface (BCI) based on motor imagery. Bandpass‐filtering EEG into several subbands related to brain activity tasks is an effective…
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Keywords:
optimal channel;
feature;
channel frequency;
feature selection ... See more keywords
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Published in 2021 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22334
Abstract: When solving many regression problems, there exist a large number of input features. However, not all features are relevant for current regression, and sometimes, including irrelevant features may deteriorate the learning performance. Therefore, it is…
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Keywords:
high dimensional;
feature selection;
regression;
lssvr ... See more keywords
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Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22979
Abstract: With regard to large dimensions of contemporary data sets and restricted computational time of intelligent systems, reducing the dimensions of data sets is necessary. Feature selection is a practical way to remove a set of…
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Keywords:
whale optimization;
algorithm;
intelligent systems;
feature selection ... See more keywords
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Published in 2017 at "PROTEOMICS"
DOI: 10.1002/pmic.201700093
Abstract: Identifying reproducible yet relevant protein features in proteomics data is a major challenge. Analysis at the level of protein complexes can resolve this issue and we have developed a suite of feature‐selection methods collectively referred…
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Keywords:
class;
analysis;
protein;
feature selection ... See more keywords
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Published in 2018 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1240
Abstract: Feature selection has been an important issue in machine learning and data mining, and is unavoidable when confronting with high‐dimensional data. With the advent of multilabel (ML) datasets and their vast applications, feature selection methods…
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Keywords:
comprehensive review;
selection;
feature selection;
multilabel feature ... See more keywords
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Published in 2020 at "European Journal of Nuclear Medicine and Molecular Imaging"
DOI: 10.1007/s00259-020-04771-5
Abstract: Purposes To evaluate the capability of PET/CT images for differentiating the histologic subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from radiomics-based machine learning/deep learning algorithms. Methods In this study,…
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Keywords:
machine;
feature selection;
pet images;
accuracy ... See more keywords
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Published in 2020 at "Engineering with Computers"
DOI: 10.1007/s00366-020-01028-5
Abstract: Feature selection is a required preprocess stage in most of the data mining tasks. This paper presents an improved Harris hawks optimization (HHO) to find high-quality solutions for global optimization and feature selection tasks. This…
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Keywords:
feature selection;
ihho;
selection;
hho ... See more keywords
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Published in 2021 at "Engineering With Computers"
DOI: 10.1007/s00366-021-01369-9
Abstract: Feature selection (FS) is a critical step in data mining, and machine learning algorithms play a crucial role in algorithms performance. It reduces the processing time and accuracy of the categories. In this paper, three…
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Keywords:
optimization;
feature selection;
optimization algorithm;
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Published in 2017 at "Soft Computing"
DOI: 10.1007/s00500-016-2189-8
Abstract: The dynamic Web, which contains huge number of digital documents, is expanding day by day. Thus, it has become a tough challenge to search for a particular document from such a large volume of collections.…
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Keywords:
classification;
feature selection;
feature;
text data ... See more keywords