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I have RF spectra of various samples consisting of 5 components in the frequency range of 10MHz to 1000MHz, 1000-2000MHz and so on. I need to predict one of the component in an unknown sample. can anybody please help me on how to represent the data and which ML algorithms to be used?

molbdnilo
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Sulaxana Vernekar
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  • So one column is the target or you need to predict values from all columns? Also could you explain what do you mean by 'unknown sample'. – itogaston Aug 17 '22 at 08:16
  • one column is the target. Unknown sample means a spectra where the concentrations of the components in the sample are not known. the concentration of the required component will be predicted using the model created. – Sulaxana Vernekar Aug 19 '22 at 06:01

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I would suggest looking at sklearn imputer module. It sounds like you have what is know as missing values. There is a couple of ways of imputing those values.

From the simplest way (imput always some value). To imputing based on the mean or median of the column. Or using something more fancy like the Iterative Imputer.

At the end you just want to fill the gaps to be able to use some of the ml models. There are some models (like the trees and forest I believe) that can handle missing values but they don't perfom as good as using imputation.

Let me know if this was helpful or I misunderstood your problem.

itogaston
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I believe you are trying to find pitch of the unlabeled audio sequence. I'm attaching a link of another question, please view it. link: Trying to get the frequencies of a .wav file in Python

Muhammad Ahmed
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