regression technique meaning in English
回归技术
Examples
- The safe selective regression technique based on multilayer functional model was carried out in the project of the china union pay system integration te - sting - the switch subsystem functional testing . it is indicated that the technique is flexible , effective and practicable
最后本文结合中国银联信息处理中心系统集成测试-转接子系统功能测试测试实例，说明该技术是一项灵活有效并且十分实用的回归测试技术。 - Global motion can be modeled by a few parameters will be stated in chapter 2 . in chapter two are given the system structure and key technologies of global estimation and compensation , describing several possible details of each key technology . global motion parameters estimated using regression technique which first estimate the local motion and then uses the local information to find the global motion that minimize the least square error
并重点研究了一种基于回归分析的图像全局运动估计与补偿技术,它首先利用光流场法估计局部图像背景点的速度场,然后利用鲁棒的叠代排除法估计图像传感器的全局运动模型参数,再利用估计出来的全局运动参数对图像进行双线性内插运动补偿。 - Today , the third party of software testing is taking part in testing process . as the functional testing is very important for the third part of software testing , and the test for relationship between operations has attached importance , it is practical to investigate the regression technique based on function and operation specifications
现阶段，软件测试第三方逐渐介入到软件测试过程中，功能测试是其中一项重要内容，而且对业务流程间联系的测试渐渐受到重视，所以基于功能的、同时考虑业务需求的回归测试技术研究具有重要的现实意义。 - Up to now , there are many software regression testing techniques , such as retest all regression technique , random select regression technique , minimization regression technique , data flow regression technique , safe regression technique etc . . however , all these techniques are code - based
到目前为止，已经有很多软件回归测试技术，其中具有代表性的几种技术是全部回归测试技术，随机选择回归测试技术，最小化回归测试技术，数据流回归测试技术，安全回归测试技术等。 - Evidence suggests that the prognostic ability of the new model with high stability , when hidden nodes changing nearby input nodes and training times changing at the certain extent , is significantly better than traditional step wise regression model mainly due to the new model condensing the more forecasting information , properly utilizing the ability of ann self - adaptive learning and nonlinear mapping . but the linear regression technique only selects several predictors by the f value , many predictors information with high relative coefficients is not included . so the new model proposed in this paper is effective and is of a very good prospect in the atmospheric sciences fields
进一步深入分析研究发现，本文提出的这种基于主成分的神经网络预报模型，预报精度明显高于传统的逐步回归方法，其主要原因是这种新的预报模型集中了众多预报因子的预报信息，并有效地利用了人工神经网络方法的自组织和自适应的非线性映射能力；而传统的逐步回归方法是一种线性方法，并且逐步回归方法只是根据f值大小从众多预报因子中选取几个预报因子，其余预报因子的预报信息被舍弃。