SVM 为每个输入输出相同的预测值……这是为什么呢？答案

【问题标题】：SVM outputting the same prediction value for every input... Why is that?SVM 为每个输入输出相同的预测值……这是为什么呢？
【发布时间】：2013-10-30 13:33:54
【问题描述】：

我使用 Encog 并使用 SVM 来预测数据。我的训练集值没有标准化，但它们最初在 [-1,1] 范围内。我不明白为什么会出现问题。

我的训练数据：

EURUSD_OPEN_CH,EURUSD_HIGH_CH,EURUSD_LOW_CH,EURUSD_CLOSE_CH,EURUSD_MACD,EURUSD_MACDS,EURUSD_STTDEV
 0.0134883819,0.0132838637,0.0135361889,0.0140344719,0.0023983892,0.0010403195,0.0054870487
 0.0001454143,0.0000969039,-0.0002216665,-0.0005261919,0.0035244907,0.0013168603,0.0070012526
 -0.0005261846,0.0006574986,0.0001593581,0.0009628839,0.0044774819,0.0017225556,0.0081131621
 0.0009282350,-0.0001867452,-0.0004156506,-0.0005882475,0.0051052958,0.0021969854,0.0088044648
 -0.0005605769,-0.0006641071,0.0001455382,0.0000069246,0.0055397905,0.0027231400,0.0092672117
 (...)

我应该标准化这些值吗？我认为这不是问题，但谁知道......我训练了 SVM，一切似乎都正确，但是当我评估 SVM 时，每个输入的输出都是相同的。如果需要，我可以附上代码。

【问题讨论】：

"如果有必要我可以附上代码。" -- 是的，通常是一个不错的选择。

标签： svm encog

【解决方案1】：

我是个菜鸟……规范化解决了这个问题。这些值太小而无法预测，因此我将整个 CSV 标准化为 [0.1,0.9] 范围，这很有帮助。

【讨论】：

感谢您帮助另一个“菜鸟”解决不同的问题。
之后你如何去规范化它？