Cited By
View all- Nicola VDelgado KLauretto M(2024)Imbalance-Robust Multi-Label Self-Adjusting kNNACM Transactions on Knowledge Discovery from Data10.1145/366357518:8(1-30)Online publication date: 26-Jul-2024
As data streams become more prevalent, the necessity for online algorithms that mine this transient and dynamic data becomes clearer. Multi-label data stream classification is a supervised learning problem where each instance in the data stream is ...
The problem of mining single-label data streams has been extensively studied in recent years. However, not enough attention has been paid to the problem of mining multi-label data streams. In this paper, we propose an improved binary relevance method to ...
Data stream classification is an important research direction in the field of data mining, but in many practical applications, it is impossible to collect the complete training set at one time, and the data may be in an imbalanced state and ...
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