Results 161 to 170 of about 2,231 (201)

Predicting cervical cancer among women living with HIV/AIDS at public health facilities in a resource-limited setting in Ethiopia using machine learning analysis. [PDF]

Discov Oncol
Mengistie MB, Mengstie SK, Teferi GH, Shume AW, Ayalew WL, Ayalew ML, Mengistu AK, Tizie SB, Gebeyew AS, Terefe MK, Enyew LM.   +10 more
europepmc   +1 more source

Non-technical loss detection in power distribution networks using machine learning. [PDF]

Sci Rep
Abro SA, Laghari JA, Memon SA, Khan TA, Memon I, Nasir H, Fatima K.   +6 more
europepmc   +1 more source

Interpretable Machine Learning for Predicting Adverse Pregnancy Outcomes in Gestational Diabetes: Retrospective Cohort Study. [PDF]

JMIR Med Inform
Li J, Liu X, He S, Ren Y.
europepmc   +1 more source

Classification Of Imbalanced Data On Crotonylation Sites Using Lightgbm With Adasyn Oversampling

Favorisen R. Lumbanraja, Ardella Dean Awalia, Sri Karnila, Mohammad Reza Faisal, null Aristoteles, Akmal Junaidi   +5 more
openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Telecom Fraud Identification Based on ADASYN and Random Forest

2020 5th International Conference on Computer and Communication Systems (ICCCS), 2020
With the development of information and communication technology, the situation of communication frauds is becoming more and more serious, how to identify fraudulent telephone accurately and effectively has become an urgent task in telecom operation at present.
Shaofu Lin
exaly   +2 more sources

ADASYN and ABC-optimized RBF convergence network for classification of electroencephalograph signal

Personal and Ubiquitous Computing, 2021
Electroencephalograph (EEG) is supposed to be a major challenge in the area of biomedical signal processing. Being one of the widely used invasive techniques, it is capable to find many cases of brain disorder problems like epileptic seizures and sleep disorder.
Sandeep Kumar Satapathy, Shruti Mishra, Pradeep Kumar Mallick   +2 more
exaly   +2 more sources

An Explainable ADASYN‐Based Focal Loss Approach for Credit Assessment

Journal of Forecasting
ABSTRACTThe integration of deep learning techniques with financial technology (fintech) has revolutionized the credit risk analysis, a critical component of financial risk management. A pervasive challenge in credit risk assessment lies in the skewed distribution of data, hindering accurate predictions, particularly for minority class instances.
Shaukat Ali Shahee, Rujavi Patel
exaly   +2 more sources

AR-ADASYN: angle radius-adaptive synthetic data generation approach for imbalanced learning

Statistics and Computing
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hyunjoong Kim, Kim Hyunjoong
exaly   +2 more sources

An Intrusion Detection Method Using ADASYN and Bayesian Optimized LightGBM

2022 34th Chinese Control and Decision Conference (CCDC), 2022
Minrui Fei, Dajun Du, Aleksandar Rakic   +2 more
exaly   +2 more sources

Network Intrusion Detection Model Based on PCA + ADASYN and XGBoost

Proceedings of the 2020 3rd International Conference on E-Business, Information Management and Computer Science, 2020
Due to the class-imbalance and redundancy of sample features, the network intrusion detection model based on classification algorithm has high false positive rate (FPR) for minority sample. A network intrusion detection model based on PCA + ADASYN and XGBoost is proposed. The principal component analysis (PCA) algorithm is used to reduce the redundancy
Leilei Pan, Xiaolan Xie
openaire   +1 more source