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Total 41건 1 페이지
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41

Expert Systems with Applications, 240, 122288

2024

This paper presents a novel end-to-end oversampling-classification approach, which we refer to as imbalanced data-classifying generative adversarial network (ImbGAN), for imbalanced data classification. ImbGAN has a classifier-embedded structure within a GAN a…

23.11.17 197
Link
40

Applied Soft Computing, 147, 110742

2023

In semiconductor manufacturing processes, spatial defect patterns on semiconductor wafers can provide useful information to quality engineers regarding the root causes of abnormalities. As early detection of process problems increases the wafer yield, the auto…

23.08.24 276
Link
39

Applied Soft Computing, 146, 110657

2023

Density peaks clustering (DPC), which is short for clustering by fast search-and-find of density peaks, is a recently developed density-based clustering method that is widely used because of its effective detection of isolated high-density regions. However, it…

23.07.30 190
Link
38

Remote Sensing, 15(13), 3453, 1-26

2023

Stringent global regulations aim to reduce nitrogen dioxide (NO2) emissions from maritime shipping. However, the lack of a global monitoring system makes compliance verification challenging. To address this issue, we propose a systematic approach to monitor sh…

23.07.09 216
Link
37

IEEE Access, 11, 31467-31478

2023

The imbalance of classes in real-world datasets poses a major challenge in machine learning and classification, and traditional synthetic data generation methods often fail to address this problem effectively. A major limitation of these methods is that they t…

23.04.04 314
Link
36

IEEE Access, 11, 24535-24544

2023

In most manufacturing sites, the data collected from dynamic equipment systems change over time owing to facility maintenance, environmental fluctuations, and aging equipment. Therefore, previously trained predictive models tend to perform worse as time passes…

23.03.17 305
Link
35

Expert Systems with Applications, 217, 119564

2023

Imbalanced data classification is a challenging problem frequently encountered in many real-world applications. Traditional classification algorithms are generally designed to maximize overall accuracy; therefore, their effectiveness tends to be impeded by imb…

23.01.24 360
Link
34

Pattern Recognition, 127, 108639

2022

Clustering is a subjective task, that is, several different results can be obtained from a single clustering hierarchy, depending on the observation scale. A local view of the data may necessitate more clusters, whereas a global view requires fewer clusters. I…

22.03.15 885
Link
33

IEEE Access, 10, 22724-22736

2022

The naive Bayesian classification method has received significant attention in the field of supervised learning. This method has an unrealistic assumption in that it views all attributes as equally important. Attribute weighting is one of the methods used to a…

22.03.06 865
Link
32

Entropy, 24(3), 366

2022

Since the coronavirus disease 2019 (COVID-19) pandemic, most professional sports events have been held without spectators. It is generally believed that home teams deprived of enthusiastic support from their home fans experience reduced benefits of playing on …

22.03.06 817
Link
31

IEEE Access, 9, 158010 - 158026.

2021

Imbalanced data classification is one of the most important tasks in the field of machine learning because abnormality, which is usually of our interest, appears less frequently than normality in real-world systems. Learning classifiers from imbalanced data ca…

21.12.06 963
Link
30

Applied Sciences, 11(19), 8977.

2021

Two-way cooperative collaborative filtering (CF) has been known to be crucial for binary market basket data. We propose an improved two-way logistic regression approach, a Pearson correlation-based score, a random forests (RF) R-square-based score, an RF Pears…

21.10.22 1129
Link
29

ACS Nano, 2020, ASAP (Open access via ACS Editors' Choice)

2020

Although transmission electron microscopy (TEM) may be one of the most efficient techniques available for studying the morphological characteristics of nanoparticles, analyzing them quantitatively in a statistical manner is exceedingly difficult. Herein, we re…

20.12.19 1802
Link
28

Automation in Construction, 110, 102974.

2020

The purpose of this study is to develop a prediction model that identifies the potential risk of fatality accidents at construction sites using machine learning based on industrial accident data collected by the Ministry of Employment and Labor (MOEL) of the R…

20.12.19 1709
Link
27

IEEE Access, 7, 106034-106042.

2019

This paper presents a modification of Quinlan's C4.5 algorithm for imbalanced data classification. While the C4.5 algorithm uses the difference in information entropy to determine the goodness of a split, the proposed method, which is named AUC4.5, examines th…

20.12.19 1548
Link

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