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pythonfftdimensionality-reduction

fourier transformation as a dimensional reduction technique in python

My dataset has 2000 attributes and 200 samples. I need to reduce the dimensionality of it. To do this, I am trying to use Fourier transformation as a dimensional reduction. Fourier transformation returns the discrete Fourier transform when I feed data as an input. But I do not know how to use it for dimensional reduction. 

from scipy.fftpack import fft
import panda as pd

price = pd.read_csv(priceFile(), sep=",")
transformed = fft(price )

Can you please help me?

Solution

  • Fourier transform is most suited if your samples are each a time series. If they are you may extract frequency domain features for each sample from transformed. Here is a listing of common features in time and frequency domain that you can consider (reference):

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