Fig. 2 Multivariate regression tree for associations classification.
图2群丛分类多元回归树。
Objective To investigate on the more accurate pruning strategies of regression tree.
目的探讨树型回归模型更为准确的剪枝技术。
For analysis of genomic data, regression tree approaches to the analysis of interactions between genes and between genes and the environment will be used.
对于基因数据，则采用回归树分析基因与基因之间、基因与环境之间的交互作用。
Conclusion Regression tree also has its application condition, these condition should be checked before analysis, correspond step should be applied when necessary.
结论虽然树模型是非参数分析方法，但回归树仍有其适用条件，在使用时需要对这些条件加以检查，必要时应采取相应的处理措施。
It is shown by the CART test that the classification and regression tree can satisfactorily accomplish the task of classification and prediction of the joint of welded spot.
CART测试结果表明，分类回归树可以较为满意地完成焊点接头强度的分类、预测任务。
Results Default arithmetic of regression tree can't be used directly under the condition of non-normal distribution, existence of outlier would make the problem more severity.
结果当应变量非正态分布时，直接应用现有回归树算法不能得出正确的分析结论；而当存在极端值时这一问题更为严重。
A binary tree classifier based on multivariate step-wise regression was designed and implemented.
作者设计并实现了一个基于多变元逐步回归的二叉树分类器。
Based on the data of forest resources inventories of Henan Province in 2003, forest biomass carbon storage is estimated using regression equation between biomass of various tree species and volume.
利用2003年河南省森林资源清查资料，建立不同优势树种生物量与蓄积量之间的回归方程，对河南省森林的碳储量进行了推算。
As showed the curve regression equations of tree height-age relations matched the sample data nicely and reflected the trees' grown process nicely.
这表明，筛选拟合的树高——年龄导向曲线回归方程很好地拟合了样本资料，很好地反映了树高的生长过程。
As showed the curve regression equations of tree height-age relations matched the sample data nicely and reflected the trees' grown process nicely.
这表明，筛选拟合的树高——年龄导向曲线回归方程很好地拟合了样本资料，很好地反映了树高的生长过程。
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