Optimize Feature Engineering Part 2 #9
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* Applied scalar multiplication to vector * Used indexing technique * Transformed from float64 to float32
This is an expected behavior (confirmed by Chaozhong), but not sure why. We can ignore this anyway. |
hyunhwan-bcm
reviewed
Jul 2, 2024
| for i in range(0, max_iter): | ||
| Fs = np.append(Fs, F, axis=1) | ||
| F = alpha * nn @ Fs[:, [i]] + fY | ||
| F = nn @ (alpha * Fs[:, [i]]) + (1 - alpha) * y |
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any benefit for using (1 - alpha) * y instead of using fY?
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any benefit for using
(1 - alpha) * yinstead of usingfY?
I thought it adds intuitiveness to the equation, and no drawbacks on speed.
Because I used float32 instead of float64, for the purpose of speed optimization, but not necessary. It only improves 30s. |
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Changed Output
There's subtle change on outputs, but I think they are ignorable.
Reduced the running time
Before:
After: