Creating the regression model with weka.
用WEKA创建一个回归模型。
This tells WEKA that we want to build a regression model.
这会告诉WEKA我们想要构建一个回归模型。
Regression model fitting results are not so satisfying.
线性回归模型的拟合效果总体较差。
This regression model is easy to use and can be used for myriad data sets.
这个回归模型很容易使用，并且可以用于很多数据集。
It puts the regression model right there in the output, as shown in Listing 2.
它会把这个回归模型径直放在输出，如清单2所示。
Now that the data file has been created, it's time to create our regression model.
数据创建完成后，就可以开始创建我们的回归模型了。
He has used a tool of economic analysis, called a vector auto-regression model.
他使用了一个被称为“向量自回归模型”的经济分析工具。
Examples on volume equation of multiplicative regression model are illustrated.
例举了乘法回归模型的材积方程的应用实例。
Objective To sump up and extend COX regression model with categorical variables.
目的总结和推广包含分类变量的COX模型。
We change the truncated regression model into the semiparametric regression model.
将截断数据回归模型转化成半参数回归模型。
This paper forecasts the sales volume of business house and service by regression model.
本文通过建立的回归模型，对商服用房的销售量进行了预测。
Spatial distribution of TN content could be forecasted by using linear regression model.
利用线性回归模型，可以预测TN含量的空间分布。
Changing variable, set up a regression model, take regression analyse using sample data.
选择变量，建立回归模型，代入样本数据进行回归分析。
A multivariate regression equation was deduced with a multivariate linear regression model.
通过多元线性回归模型，得出了多因子复合流变方程。
The results from regression model further reinforce the findings of the causality analysis.
计量分析的结果则进一步加强了这一发现。
So it's not a problem, computationally, to create a powerful regression model from a lot of data.
所以，即使要处理的是具有大量数据的功能强大的回归模型，就计算而言，也不是什么问题。
Selecting a stochastic regression model is an important question in regression analysis theory.
随机回归模型的选择是回归分析理论中的重要问题之一。
So this regression model is telling us that granite in your kitchen doesn't affect the house's value.
所以这个回归模型告诉我们厨房里的花岗石并不会影响房子的价值。
It mainly researches the rationality of regression model and the independent variables selection.
主要研究模型假设的合理性和自变量的选择。
Let's continue this example of a house price-based regression model, and create some real data to examine.
让我们继续以这个房屋定价的回归模型为例，创建一些真实的数据。
The study shows that the precision of the improved model is better than the stepwise regression model.
实例分析表明，该模型的精度要比逐步回归模型高。
Regression model showed that the variation of abstract word number was 0.021 ~ 0.044 with thesis length.
不同中图分类号论文的回归模型表明，文摘字数随论文篇幅的变化率为0.021～0.044；
Everyone has probably used or seen a regression model before, maybe even mentally creating a regression model.
每个人都可能使用过或看到过回归模型，甚至曾在头脑里创建过一个回归模型。
This paper presents regression model with same regression coefficient and different regression constants.
本文讨论回归系数相同，回归常数不同的回归分析模型。
So, if you've ever bought a house or sold a house, you've likely created a regression model to price the house.
所以，不管是购买过一个房子还是销售过一个房子，您都可能会创建一个回归模型来为房子定价。
There is a regression constant in the linear regression model. But it is not significant in some conditions.
利用线性回归建模时，一般都采用有常数项的模型，而不去考虑它对回归的作用是否显著。
Let's put our data through the regression model and make sure the output matches the output we computed using the Weka Explorer.
让我们把我们的数据通过回归模型进行处理并确保输出与我们使用WekaExplorer计算得到的输出相匹配。
Running a classification, clustering, or Nearest Neighbor isn't quite as easy as a regression model, but they aren't much harder.
运行分类、群集或最近邻都不如回归模型简单，但它们也没有那么困难。
The regression model is then used to predict the result of an unknown dependent variable, given the values of the independent variables.
然后用回归模型根据给定的这些自变量的值预测一个未知的因变量的结果。
The regression model is then used to predict the result of an unknown dependent variable, given the values of the independent variables.
然后用回归模型根据给定的这些自变量的值预测一个未知的因变量的结果。
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