Results 151 to 160 of about 3,838 (180)

Precise Discrimination Between Rape Honey and Acacia Honey Based on Sugar and Amino Acid Profiles Combined with Machine Learning. [PDF]

Foods
Sun C, Pan F, Tian W, Cui Z, Xue X, Xu Y.   +5 more
europepmc   +1 more source

AS-TBR: An Intrusion Detection Model for Smart Grid Advanced Metering Infrastructure. [PDF]

Sensors (Basel)
Ma H, Fan Y, Zhang Y.
europepmc   +1 more source

Development and validation of a practical prediction model for post-ERCP pancreatitis using machine learning. [PDF]

Front Surg
De T, Du G, Yin H, Wang H, Wang W, Ma T, Ma J, Wang H, Wang Q.   +8 more
europepmc   +1 more source

Integrating machine learning and explainable AI for employee attrition prediction in HR analytics. [PDF]

Sci Rep
Al-Ali M, Alwateer M, Alsaedi SA, Balaha HM, Badawy M, A Elhosseini M.   +5 more
europepmc   +1 more source

Predicting road traffic accident severity from imbalanced data using VAE attention and GCN. [PDF]

Sci Rep
Shangguan A, Feng N, Hei X, Fei R, Jin Y, Mu L, Li Y.   +6 more
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

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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.
Chao Lu, Shaofu Lin, Xiliang Liu, Hui Shi   +3 more
openaire   +1 more source

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

MIAC: Mutual-Information Classifier with ADASYN for Imbalanced Classification

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2018
currently, classification of imbalanced data is a significant issue in the area of data mining and machine learning because of the imbalance of most of the data set. An effective solution of this problem is Cost-Sensitive Learning (CSL), but when the costs are not given, this method cannot work property.
Yanyu Cao, Xiaodong Zhao, Zhiping Zhou, Yufei Chen, Xianhui Liu, Yongming Lang   +5 more
openaire   +1 more source

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, Gyoo-Soo Chae   +3 more
openaire   +1 more source