Data pre - processing for artificial Neural Network

2 次查看(过去 30 天)
Hi everyone, I have a question. I am using the advance scripts made by Matlab for the creation of neural networks (by neural network tool).
In input to the network I gave power values ​​that had been statistically Normalized.
Once I finished training the network I realized that there is already a pre - processing function within the script that allows you to Normalize the data using the maximum and minimum values.
What I now ask myself is, are the results I got from the network, having both standardized and normalized max-min data correct? Or is it nonsense?

采纳的回答

Tarunbir Gambhir
Tarunbir Gambhir 2020-12-21
Min-Max Normalization is usually done when the data has varying scales and the training model does not make any assumptions about the distribution of data. Like Artificial Neural Network, or K-nearest neighbours.
Standardization assumes that the data has a Gaussian distribution, and therefore is generally employed when the data has varying scales and the training algorithm assumes that the data follows a Gaussian distribution. Like linear regression, logistic regression, or linear discriminant analysis.
If your data does follow a Gaussian distribution, performing standardization on top of min-max normalization should give you the desired results despite being an extra step.

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Statistics and Machine Learning Toolbox 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by