1
$\begingroup$

I have a spectrogram of a signal and want to classify it. I used different features such as MFFC, the density of power spectrum and other common features and classify using the random forest, but I did not get good results.

I think that my features are not well selected and I guess that there is no relation between my aimed classes and the selected features. my classes are so rare.

could anyone suggest a way for obtaining features?(for very rare data) also, I used some methods of feature extraction from biological images, but I think that the data are different. my data are double and those are some 3 dimensions data.

$\endgroup$

1 Answer 1

2
$\begingroup$

Try one of Arizona State - Feature Selection Algorithms for feature selection:

BLogReg  
CFS  
Chi Square  
FCBF  
Fisher Score  
Gini Index  
Information Gain  
Kruskal-Wallis  
mRMR  
Relief-F  
SBMLR  
T-test  
SPEC
$\endgroup$
3

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.