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

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. To solve this problem, many variations of synthetic m...

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Bibliographic Details

Published in:	Applied System Innovation
Main Authors:	Mimi Mukherjee, Matloob Khushi
Format:	Article
Language:	English
Published:	MDPI AG 2021-03-01
Subjects:	SMOTE nominal feature continuous feature class imbalance precision recall
Online Access:	https://www.mdpi.com/2571-5577/4/1/18