Results 71 to 80 of about 224,004 (328)

CLASSIFICATION BOOSTING IN IMBALANCED DATA

Malaysian Journal of Science, 2019
Most existing classification approaches assumed underlying training data set to be evenly distributed. However, in the imbalanced classification, the training data set of one majority class could far surpass those of the minority class. This becomes a problem because it’s usually produces biased classifiers that have a higher predictive accuracy over ...
Sinta Septi Pangastuti, Kartika Fithriasari, Nur Iriawan, Wahyuni Suryaningtyas   +3 more
openaire   +2 more sources

Patatin‐domain‐containing (phospho)lipases under control: Mammalian co‐regulators and pathogenic activation mechanisms

FEBS Open Bio, EarlyView.
Patatin domain‐containing (phospho)lipases are lipid‐hydrolyzing enzymes central to metabolism, membrane remodeling, and signaling. Their activity relies on precise co‐activation mechanisms involving protein–protein interactions and conformational rearrangements.
Noopur Dubey, Lina Riegler‐Berket, Monika Oberer   +2 more
wiley   +1 more source

A Classification Method Based on Feature Selection for Imbalanced Data

IEEE Access, 2019
Imbalanced data are very common in the real world, and it may deteriorate the performance of the conventional classification algorithms. In order to resolve the imbalanced classification problems, we propose an ensemble classification method that ...
Yi Liu, Yanzhen Wang, Xiaoguang Ren, Hao Zhou, Xingchun Diao   +4 more
doaj   +1 more source

Integrative machine learning approach for multi-class SCOP protein fold classification [PDF]

, 2003
Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP classification, most discriminative machine learning suffers the well-known ‘
Deville, Y, Gilbert, D, Tan, A C
core  

Erythropoietin modulates hepatic inflammation, glucose homeostasis, and soluble epoxide hydrolase and epoxides in high‐fat diet‐induced obese mice

FEBS Open Bio, EarlyView.
Erythropoietin administration suppresses hepatic soluble epoxide hydrolase (sEH) expression, leading to increased CYP‐derived epoxides. This is associated with a shift in hepatic macrophage polarization characterized by reduced M1 markers and increased M2 markers, along with reduced hepatic inflammation, suppressed hepatic lipogenesis, and attenuated ...
Takeshi Goda, Satoru Sugimoto, Chiharu Cho, Madoka Konishi, Nozomi Inoue, Satoshi Miyagaki, Yasuhiro Kawabe, Takuro Okamura, Masahide Hamaguchi, Hisakazu Nakajima, Michiaki Fukui, Masakazu Shinohara, Tomoko Iehara   +12 more
wiley   +1 more source

DPC-SMOTE Over-sampling Algorithm for Imbalanced Data Classification

Journal of Harbin University of Science and Technology
An oversampling algorithm based on density peak clustering is proposed to solve the problem of noise and imbalance among classes in imbalanced data sets.
LIU Zhihan, ZHANG Zhonglin, ZHAO Lei
doaj   +1 more source

A novel imbalanced data classification approach for suicidal ideation detection on social media [PDF]

, 2021
Mohamed Ali Ben Hassine, Safa Abdellatif, Sadok Ben Yahia   +2 more
openalex   +1 more source

The Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential

Aging and Cancer, EarlyView.
As a conduit linking all organs, the blood system both reflects and actively drives systemic aging. This review highlights how circulating pro‐aging and antiaging factors and age‐associated hematopoietic stem cell dysfunction contribute to immunosenescence and multi‐organ decline, positioning the hematopoietic system as a target for aging intervention.
Hanqing He, Jianwei Wang
wiley   +1 more source

Partial Resampling of Imbalanced Data

, 2022
Imbalanced data is a frequently encountered problem in machine learning. Despite a vast amount of literature on sampling techniques for imbalanced data, there is a limited number of studies that address the issue of the optimal sampling ratio. In this paper, we attempt to fill the gap in the literature by conducting a large scale study of the effects ...
Kamalov, Firuz, Atiya, Amir F., Elreedy, Dina   +2 more
openaire   +2 more sources

Relapsing–Remitting Multiple Sclerosis Is Associated With a Dysbiotic Oral Microbiome

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammation, demyelination, and neurological impairment. While the gut microbiota's role in MS is extensively studied, the association between the oral microbiota and MS remains underexplored, particularly in North American cohorts.
Sukirth M. Ganesan, Meeta Yadav, Sudeep Ghimire, Peter C. Lehman, Apurva J. Patel, Sydney Woods, Heena Olalde, Jemmie Hoang, Mishelle Paullus, Catherine Cherwin, Christine Gill, Tracey Cho, Ashutosh K. Mangalam   +12 more
wiley   +1 more source