Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…Responding to overcome this problem, the work at hand implements ten top-performing Synthetic Minority Oversampling Technique (SMOTE) variants. The models’ performances balanced by each SMOTE variant are analyzed and compared. …”

The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

“…Our results showed that the replacement method was effective, and LogisticRegression combined with the oversampling algorithms SMOTE or ADASYN, GaussianProcessClassifier with the oversampling algorithm SMOTE, and LinearDiscriminantAnalysis were the best performing models after log transformation of the dataset was followed by Recursive Feature Elimination.…”

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…Synthetic Minority Oversampling Technique(SMOTE) and Adaptive Synthetic Sampling(ADASYN) are some of the commonly used techniques to deal with class imbalance. …”

Performance Prediction Using Classification by MOOLIYIL, GITA

“…A comprehensive evaluation requires that multiple models with different algorithms were analyzed using key performance measures. …”
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Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”