提出了一种大规模数据集的训练样本选择方法。
A new method is proposed for sample selection in large data set.
本文主要从训练样本选择和预测算法两个方面进行了研究。
The paper studied Ultra-short term the load forecasting from two aspects:data preprocessing and forecast method.
以入侵检测系统中的分类器设计为例，研究分类器训练样本选择问题。
Taking the example of designing classifier in intrusion detection system, the selection of training samples for classifier is studied.
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