cpajournal

Automating Data Analysis with Python Dashboards

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...
IEEE

Oversampling with GAN via meta-learning for imbalanced data

Abstract: Utilizing generative adversarial networks (GANs) for oversampling imbalanced data has demonstrated its effectiveness. However, many GAN-based oversampling methods are confronted with a ...
Scientific Research Publishing

Fernandez, A., Garcia, S., Herrera, F. and Chawla, N.V. (2018) SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-Year Anniversary. Journal of ...

ABSTRACT: A degenerative neurological condition called Parkinson disease (PD) that evolves progressively, making detection difficult. A neurologist requires a clear healthcare history from the ...
Scientific Research Publishing

Mukherjee, M. and Khushi, M. (2021) SMOTE-ENC: A Novel Smote-Based Method to Generate Synthetic Data for Nominal and Continuous Features. Applied System Innovation, 4, Article 18.

ABSTRACT: Bipolar disorder is a complex psychiatric condition characterized by alternating mood episodes, ranging from depression to mania. Accurate and timely detection of a patient’s current mood ...
Frontiers

Physical health and cognitive ability factors in predicting retirement adjustment based on machine learning approach: results from the China Health and Retirement Longitudinal ...

Introduction: Retirement is one of the most significant status changes in an individual's later life. Physical health and cognitive ability are key predictors of retirement adjustment. However, ...