“神经网络和Preprocessing Data"
chaosbringer
MemberPosts:21
Maven
Hi,
i have a question (of course) ;D
Is data preprocessing for neural nets beyond normalization reasaonble?
In especially:
a) Can standardization be benefical?
b) Have strongly correlated attributes a negative effect on the net?
c) May PCA be adviseable?
d) My distribution is strongly inbalanced, having a few high values and a lot very very low values. Is that a problem?
Thank you very much.
i have a question (of course) ;D
Is data preprocessing for neural nets beyond normalization reasaonble?
In especially:
a) Can standardization be benefical?
b) Have strongly correlated attributes a negative effect on the net?
c) May PCA be adviseable?
d) My distribution is strongly inbalanced, having a few high values and a lot very very low values. Is that a problem?
Thank you very much.
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0
Answers
to cut it short: 4 times Yes. But also: 4 times: Depends.
In more detail: You really can't say what will help for your data. Just try it and you will know (if you take into account all needed considerations about estimating performance).
You just can't say what will help without taking the data into account, you can't say which learner is better or which preprocessing. Everything depends on the data...
Greetings,
Sebastian