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Feature selection is beneficial for improving the performance of general machine learning tasks by extracting an informative subset from the high-dimensional features. Conventional feature selection methods usually ignore the class imbalance problem, thus the selected features will be biased towards the majority class. Considering that F-measure is a more reasonable performance measure than accuracy...
Prediction on complex time series has received much attention during the last decades. Global model is the main tool for time series predicting during the last decades, but it suffers low prediction efficiency, low prediction accuracy and high computation complexity for model training and updating. In recent years, local model for time series prediction draws widely attention for its more accuracy...
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