Numerical test results show that SVR has good ability of modeling nonstationary financial time series and good generalization under small data set available.
数值实验表明,SVR方法对非平稳的金融时间序列具有良好的建模和泛化能力。
Objective the method of three-dimension reconstruction with small data set was presented and then was used to investigate location and shape of the brain nucleus.
目的探索小数据量条件下三维重建方法,并用之研究脑内神经核团的空间形态和位置。
There are usually few training samples in the tasks of content-based remote sensing image retrieval, which will lead to over-learning problem while using this small data set for training.
提出一种基于多分类器协同训练的遥感图像检索方法,该方法在不同特征集上分别建立分类器,利用不同分类器的协同性自动标记未知样本,从而有效解决了小样本问题。
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