1) large scale data
大规模数据
1.
The problems which exist when large scale data are trained and classified are presented, and typical solutions.
介绍了支撑矢量机的分类机理 ,并针对大规模数据讨论其训练和分类中存在的问题及典型的解决方法 。
2.
An efficient target recognition method for large scale data is proposed in this paper,which is based on self-organizing map (SOM) neural network and support vector machines (SVMs).
本文提出了一种基于自组织特征映射神经网络 (SOM)和支撑矢量机 (SVM)相结合的复杂模式的大规模数据的分类方法 。
2) Massive measured data
大规模测量数据
3) large volume data sets
大规模体数据场
1.
Research on real time rendering of large volume data sets on PC hardware;
基于PC机的大规模体数据场实时可视化
4) VLDB
大规模数据库
1.
Finally,the backup and recovery model for a reality multi-node very large database(VLDB) system is realized and the rationality and usability of this model are proved.
通过在一个实际的、由多个数据库节点组成的大规模数据库系统平台上对该备份恢复模型的实现和应用,证明了该模型的合理性和可用性。
5) large-scale data set
大规模数据集
1.
More importantly, it still can be used even if traditional eigen-decomposition technique cannot be applied when faced with the extremely large-scale data set.
提出一种大规模数据集求解核主成分的计算方法。
6) large scale training data
大规模训练数据
1.
New method of SVM learning with large scale training data;
大规模训练数据的支持向量机学习新方法
补充资料：规模经济/规模不经济
规模经济/规模不经济：规模经济和规模不经济用来说明厂商产量变动从而规模变动与成本之间的关系。对于一个生产厂商而言，如果产量扩大一倍，而厂商的生产成本的增加低于一倍，则称厂商的生产存在着规模经济；如果产量增加一倍，而成本的增加大于一倍，则生产存在着规模不经济。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条