Results 251 to 260 of about 18,911 (296)
AI-ECG classification for Brugada syndrome: A study of machine learning techniques to optimise for limited datasets. [PDF]
PLOS Digit HealthSaleh K +21 more
europepmc +1 more source
ISMOTE: A More Accurate Alternative for SMOTE
Neural Processing LettersJiuxiang Song, Jizhong Liu
openaire +1 more source
Addressing class imbalance in traumatic brain injury prognostication: A survey of resampling approaches. [PDF]
AIMS NeurosciNoor NSEM.
europepmc +1 more source
Geometric SMOTE a geometrically enhanced drop-in replacement for SMOTE [PDF]
Information Sciences, 2019 Abstract Classification of imbalanced datasets is a challenging task for standard algorithms. Although many methods exist to address this problem in different ways, generating artificial data for the minority class is a more general approach compared to algorithmic modifications.
Georgios Douzas, Fernando Bacao
exaly +4 more sources
Approx-SMOTE: Fast SMOTE for Big Data on Apache Spark [PDF]
Neurocomputing, 2021 One of the main goals of Big Data research, is to find new data mining methods that are able to process large amounts of data in acceptable times. In Big Data classification, as in traditional classification, class imbalance is a common problem that must be addressed, in the case of Big Data also looking for a solution that can be applied in an ...
Mario Juez-Gil +2 more
exaly +5 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.
Matloob Khushi, Khushi Matloob
exaly +5 more sources
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Optimal Entropy Genetic Fuzzy-C-Means SMOTE (OEGFCM-SMOTE)
Knowledge-Based Systems, 2023Karim El Moutaouakil +1 more
exaly +2 more sources
SMOTE-Text: A Modified SMOTE for Turkish Text Classification
2021One of the most common problems faced by large enterprise companies is the loss of knowhow after employee’s job replacements and quits. Creating a well-organized, indexed, connected, user friendly and sustainable digital enterprise memory can solve this problem and creates a practical knowhow transfer to new recruited personnel.
Nur Curukoglu, Alper Ozpinar
openaire +1 more source