SVM爲每個輸入輸出相同的預測值...爲什麼是這樣？

Question

我使用Encog，我使用SVM預測數據。我的訓練集值沒有進行歸一化處理，但它們最初在[-1,1]範圍內。我不明白爲什麼會出現這個問題。

我的訓練數據：

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 
(...) 

我應該正常化這些價值？我認爲這不是一個問題，但是誰知道......我訓練SVM並且一切正常，但是當我評估SVM時，每個輸入的輸出都是相同的。如果需要的話，我可以附上代碼。

Answer 1

我是這樣一個noob ...規範化解決了這個問題。這些值太小而無法預測，所以我將整個CSV歸一化到了[0.1,0.9]範圍，並且它有所幫助。