Results 61 to 70 of about 98,421 (281)

An improved SMOTE algorithm for enhanced imbalanced data classification by expanding sample generation space

Scientific Reports
Class imbalance in datasets often degrades the performance of classification models. Although the Synthetic Minority Over-sampling Technique (SMOTE) and its variants alleviate this issue by generating synthetic samples, they frequently overlook local ...
Ying Li, Yali Yang, Peihua Song, Lian Duan, Rui Ren   +4 more
doaj   +1 more source

Detecting SNP–SNP Interactions in Imbalanced Case-Control Study

IEEE Access, 2019
SNP–SNP interactions are particularly informative biomarkers regarding the genetic components of disease risk. However, SNP–SNP interaction identifications are yet limited in imbalanced case–control study.
Cheng-Hong Yang, Li-Yeh Chuang, Yu-Da Lin   +2 more
doaj   +1 more source

Generation of Controlled Synthetic Samples and Impact of Hyper-Tuning Parameters to Effectively Classify the Complex Structure of Overlapping Region

Applied Sciences, 2022
The classification of imbalanced and overlapping data has provided customary insight over the last decade, as most real-world applications comprise multiple classes with an imbalanced distribution of samples.
Zafar Mahmood, Naveed Anwer Butt, Ghani Ur Rehman, Muhammad Zubair, Muhammad Aslam, Afzal Badshah, Syeda Fizzah Jilani   +6 more
doaj   +1 more source

Imbalanced Ensemble Classifier for learning from imbalanced business school data set

, 2018
Private business schools in India face a common problem of selecting quality students for their MBA programs to achieve the desired placement percentage. Generally, such data sets are biased towards one class, i.e., imbalanced in nature.
Chakraborty, Tanujit
core   +1 more source

The cooperative regulation of miR‐221 by APE1 and AUF1 impacts p27Kip1 defining a miR signature relevant for cervical cancer

FEBS Open Bio, EarlyView.
A regulatory axis involving APE1, AUF1, and miR‐221 is proposed. Pri‐miR‐221 is processed by DROSHA and DICER to generate mature miR‐221, which targets p27Kip1 mRNA. APE1 and AUF1 compete for pre‐miR‐221 binding. Reduced APE1/AUF1 levels impair miR‐221 biogenesis, decrease p27Kip1 mRNA degradation, and promote cell cycle progression, chemoresistance ...
Matilde Clarissa Malfatti, Nicolò Gualandi, Gianluca Tell, Giulia Antoniali   +3 more
wiley   +1 more source

Imbalanced Data Parameter Optimization of Convolutional Neural Networks Based on Analysis of Variance

Applied Sciences
Classifying imbalanced data is important due to the significant practical value of accurately categorizing minority class samples, garnering considerable interest in many scientific domains.
Ruiao Zou, Nan Wang
doaj   +1 more source

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

Drilling Condition Identification Method for Imbalanced Datasets

Applied Sciences
To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep ...
Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang   +3 more
doaj   +1 more source

Effective Class-Imbalance Learning Based on SMOTE and Convolutional Neural Networks

Applied Sciences, 2023
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models from achieving satisfactory results. ID is the occurrence of a situation where the quantity of the samples belonging to one class outnumbers that of the other by a wide margin ...
Javad Hassannataj Joloudari, Abdolreza Marefat, Mohammad Ali Nematollahi, Solomon Sunday Oyelere, Sadiq Hussain   +4 more
doaj   +1 more source

Prognostic Impact of European LeukemiaNet Genetic Risk Stratification System in Adult Patients With Acute Myeloid Leukemia

Aging and Cancer, EarlyView.
This study aimed to evaluate the prognostic value of ELN2017 in predicting survival outcomes and to assess the impact of clinical and molecular factors such as age, FLT3 and NPM1 mutations, and allogeneic hematopoietic stem cell transplantation (allo‐HSCT).
Mobina Shrestha, Bishwas Mandal, Vishal Mandal, Asis Shrestha, Amir Babu Shrestha   +4 more
wiley   +1 more source