幫助
只有 numpy 的簡單神經網路。代碼回傳錯誤
代碼
pe = [1,20,-15 ... 23]
learning_rate = 1e-6
#5 generations
for i in range(5):
#sess = 60 data/12
while srss <= sess:
i0 = np.iloc[t][0]
i1 = np.iloc[t][1]
i2 = np.iloc[t][2]
...
...
i23 = np.iloc[t][23]
X = [i0, i1, i2 .... i23]
y = np.sin(x)
y_pred = i0 * pe[0] i1 * pe[1] ...... i23 * pe[23]
los = np.square(y_pred - y).sum
If srss == sess:
grad_y_pred = 2.0 * (y_pred - y)
gred_0 = gred_y_pred.sum()
gred_01 = (gred_y_pred * x).sum()
gred_02 = (gred_y_pred * x ** 2).sum()
gred_23 = (gred_y_pred * x ** 23).sum()
....
pe[0] -= learning_rate * grad_00
pe[1] -= learning_rate * grad_01
pe[2] -= learning_rate * grad_01
....
pe[23] -= learning_rate * grad_23
srss = srss 1
輸出
Traceback (most recent call last):
File "run.py", line 124, in <module>
grad_02 = (grad_y_pred * x ** 2).sum()
TypeError: unsupported operand type(s) for ** or pow(): 'list' and 'int'
值型別
- I1：124264 INT
- 輸出 Y 型別：5.343
- 輸出 Y_PREAD 總價值 EX：10.24236
- 損失型別：1.5771358927e 18
更多 我需要一個正確的功能來將 OUTPUT 的值分類為高達 0.5 或低至 0.5
uj5u.com熱心網友回復：
嘗試將X（或者是x？）轉換為 numpy 陣列而不是串列：
X = np.array([i0, i1, i2 .... i23])
轉載請註明出處，本文鏈接：https://www.uj5u.com/houduan/389946.html
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