Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance
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Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance

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Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the...