使标签成为属性-决策树过程

Eric005

你好,

我目前正在做一个使用时间序列数据的股票市场方向二元分类器的演示。我生成一个自定义属性，该属性使用系列中的实际远期数据对远期市场价格(在Label2列下)做出真/假指示(上/下)，然后我的标准标签属性是通过增强的决策树预测的值。这是我的问题，当我选择属性作为进入验证的最后一步时，我将选择市场日期和市场数据，这通常会产生大约74%的准确性。如果我也选择标签作为属性，那么它就会产生98%的预测准确率(这对我来说是荒谬的)。因此，我试图理解是什么使得将标签列为属性在预测中产生如此根本的变化——决策树是否通过窗口函数使用先前的预测来影响某种循环系统中的前向预测?这些都说得通吗?

欢迎您的反馈。下面的XML。

谢谢!

埃里克

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Thomas_Ott

如果你在测试时间序列，你会想要使用滑动窗口验证操作符。

你可能想看看我在这里更新的教程:http://www.neuralmarkettrends.com/building-an-ai-financial-market-model-lesson-iv/

JEdward

我相信在这一点上，奥特先生会比我有更多的补充。他在这方面有一系列的教程。

http://www.neuralmarkettrends.com/building-an-ai-financial-market-model-lesson-i/

简单地看一下就知道了。

对时间序列使用滑动窗口验证，否则在XVal中您将使用来自未来的示例来预测过去。

在您将其他标签设置为常规的地方，您实际上可以使用set Role将角色设置为Label1, Label2等....如果你不想让你的模特使用它们，它们不需要是常规的。

Eric005

感谢您的回复和帮助。

我意识到生成二进制控件的目标属性不正确，我现在已经在随后的安排中纠正了这一点。

在这种情况下，当我为标签设置角色(set role(2))时，它也是一个常规属性，它再次提高了准确性。

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Eric005

由于托马斯