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岭回归的英文

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"岭回归"怎么读用"岭回归"造句

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  • ridge regression

例句与用法

  • Ridge regression learning in esn for chaotic time series prediction
    岭回归学习算法及混沌时间序列预测
  • Nonlinear ridge regression modeling method based on radial basis function and its simulation research
    基于径向基函数的非线性岭回归方法及仿真研究
  • Genetic algorithm optimization based nonlinear ridge regression modeling method and its application in soft measurement
    优化的非线性岭回归方法及其在软测量中的应用
  • This article gives a program of ridge regression with sas6 . 11 version , and illustrate the method of the ridge regression by an example
    本文给出了在sas6 . 11及以上版本中实现岭回归分析的程序,用具体实例说明进行岭回归的方法。
  • It is important to apply influence analysis , computing of correlation - conefficient and charactrestic value of the design matrix and ridge regression to set models . the quality of model is developed
    数据分析:影响分析和设计矩阵的相关系数和特征值计算及岭回归技术的应用对改进模型的品质起到了重要作用。
  • Based on multi - factor orthogonal designed field experiment , the ridge regression models of seed yield components and seed yield of the 6 grass species are founded through ridge regression analysis with big samples
    摘要采用多区组多因素正交试验设计,通过大样本岭回归分析求出6种禾本科牧草种子产量因子与产量的岭回归模型。
  • The main research contents include : 1 、 this paper constructs the mixed collaborative sale forecasting model based on cpfr via integrating time series forecasting , multivariate regression and ridge regression . in addition , the model takes sale information as explanation variable
    具体研究内容包括: 1 、将时间序列预测、多元回归、岭回归相结合,并将销售信息作为销售量的解释变量,构建了cpfr流程下的混合协同预测模型。
  • However , there have still some unresolved problems : first , how to determine the number and size of the clusters automatically during the clustering process . second , how to utilize the " local " ridge regression method which including multiple regularization parameters in learning rbf network . third , those clusters in irregular form ca n ' t represented by radial basis function , thus we must find some other basis functions that can describe the irregular form
    但是仍然存在几个问题尚待解决:首先,聚类时怎样自动确定簇的个数和半径;其次,如何利用含有多个正规化参数的局部岭回归方法进行rbf网络学习;第三,如果簇的形状是不规则的,则它很难用径向基函数来描述,因此需要研究其它能代表不规则形状的簇的基函数。
  • Define a radial basis function ( rbf ) at center of each cluster and learning a two - layer neural network which consists of these rbfs , simultaneously , for the purpose of avoiding over - fitting , we make use of ridge regression method , which adding a weight penalty term including a appropriate regularization parameter on the cost function and then lead to a more smooth function
    为每一个簇的中心定义相应的径向基函数( radialbasisfunction , rbf ) ,再对这些径向基函数构成的两层神经网络进行训练,同时,为了避免产生过度拟合现象,本文采用了岭回归技术,即在代价函数中加入一个包含适当正规化参数的权值惩罚项,从而保证网络输出函数具有一定的平滑度。
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