• Creating the regression model with weka.

    用WEKA创建一个回归模型。

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  • So go ahead and create the regression model.

    继续并创建这个回归模型。

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  • Test of the regression model is simple.

    回归模型的检验比较简单。

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  • This is all the same as we saw in the regression model.

    这与我们在回归模型中看到的没有差别。

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  • 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。

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  • Regression model fitting results are not so satisfying.

    线性回归模型的拟合效果总体较差。

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  • Regression model from test data has enough high precision.

    来自试验数据的回归模型具有足够高的精确度。

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  • General regression model is a generalization of linear model.

    一般回归模型是通常线性模型的推广。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • So it is very necessary to research the restricted multivariate regression model.

    因此研究带约束的回归模型是十分必要的。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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;

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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