No, that just gives the first couple of lines from the dataset.
To select features you have to define a measure to select uncorrelated features. An example would be to select one, the drop out all that are correlated > 0.9, then select the next, etc. (you’d still need to figure out how to select 1 feature to start with, or after you’ve removed correlated features).
However, if your aim is feature selection, my advice would be to read up on several popular algorithms, both supervised and unsupervised. E.g. Orthogonal Principal Feature Selection, mRMR, LASSO, etc.
Next, I also always advise to check whether you can assess stability (for e.g. reader-noise, acquisition-noise) and use that to remove unstable features.
Joost van Griethuysen
From: Namaste Tenzin [mailto:tkun...@gmail.com]
Sent: woensdag 22 januari 2020 6:14
To: Joost van Griethuysen
Subject: Re: general understanding question
Thank you so much Joost for your answer,
so in that notebook does the code line 21 (d.head) the feature names are those selected using clustering technique? so can I test those features then into my classification?
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