Results 11 to 20 of about 23,350 (290)

FLEX-SMOTE

, 2023
FLEX-SMOTE: Synthetic Over-sampling TEchnique that Flexibly Adjusts to Different Minority Class Distributions
CHUMPHOL BUNKHUMPORNPAT (16496058)
openaire   +2 more sources

DTO-SMOTE: Delaunay Tessellation Oversampling for Imbalanced Data Sets

Information, 2020
One of the significant challenges in machine learning is the classification of imbalanced data. In many situations, standard classifiers cannot learn how to distinguish minority class examples from the others.
Alexandre M. de Carvalho, Ronaldo C. Prati   +1 more
doaj   +2 more sources

SMOTE-ENC: A Novel SMOTE-Based Method to Generate Synthetic Data for Nominal and Continuous Features [PDF]

Applied System Innovation, 2021
Real-world datasets are heavily skewed where some classes are significantly outnumbered by the other classes. In these situations, machine learning algorithms fail to achieve substantial efficacy while predicting these underrepresented instances.
Mimi Mukherjee, Matloob Khushi
openaire   +5 more sources

SMOTE-MRS: A Novel SMOTE-Multiresolution Sampling Technique for Imbalanced Distribution to Improve Prediction of Anemia

IEEE Access
Anemia is a widespread worldwide health problem that has a substantial effect on groups who are particularly susceptible. The objective of this work is to improve the diagnosis of anemia by creating a hybrid machine learning model called SMOTE-MRS.
Dimas Chaerul Ekty Saputra, Khamron Sunat, Tri Ratnaningsih   +2 more
doaj   +2 more sources

FS-SMOTE: An Improved SMOTE Method Based on Feature Space Scoring Mechanism for Solving Class-Imbalanced Problems

IEEE Access
Class-imbalance problems have become a key challenge in machine learning, often results in training too many majority samples and learning too few minority samples.
Yongjie Huang
doaj   +2 more sources

Sentimen Analisis Untuk Mengukur Kepercayaan Masyarakat Terhadap Pengadaan Vaksin Covid-19 Berbasis Bernoulli Naive Bayes

BIOS, 2022
Penelitian ini berisi tentang analisis sentimen masyarakat Indonesia pada Twitter terhadap kebijakan pemerintah dalam menangani kasus pandemi covid-19.
Hanifatul Azizah, Bagus Setya Rintyarna, Triawan Adi Cahyanto   +2 more
doaj   +1 more source

SMOTE for Regression [PDF]

, 2013
Several real world prediction problems involve forecasting rare values of a target variable. When this variable is nominal we have a problem of class imbalance that was already studied thoroughly within machine learning. For regression tasks, where the target variable is continuous, few works exist addressing this type of problem.
Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, Paula Branco   +3 more
openaire   +1 more source

On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems [PDF]

, 2011
The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data.
Hong, Xia, Gao, Ming, Chen, Sheng, Harris, Chris   +3 more
core   +2 more sources

ESSAY ANSWER CLASSIFICATION WITH SMOTE RANDOM FOREST AND ADABOOST IN AUTOMATED ESSAY SCORING

IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023
Automated essay scoring (AES) is used to evaluate and assessment student essays are written based on the questions given. However, there are difficulties in conducting automatic assessments carried out by the system, these difficulties occur due to ...
Wilia Satria, Mardhani Riasetiawan
doaj   +1 more source

Cross-Project Defect Prediction with Metrics Selection and Balancing Approach

Applied Computer Systems, 2022
In software development, defects influence the quality and cost in an undesirable way. Software defect prediction (SDP) is one of the techniques which improves the software quality and testing efficiency by early identification of defects(bug/fault/error)
Nevendra Meetesh, Singh Pradeep
doaj   +1 more source