Combining different feature vectors for, SVM training for MRI classification

Question

I've been currently working on my FYP on Brain tumor classification.Extracted features using wavelet transform ,glcm ,polynomial transform etc. IS IT RIGHT TO APPEND THESE FEATURE VECTORS (columnwise) for training? like combinations of these feature vectors eg: glcm+wavelet

Can you suggest me any papers related to this?

THANK YOU FOR THE HELP

Answer 1

Yes, this method is known as early fusion.

In other words, early fusion is when you are concatenating 2 or more features sets prior to model training.

There are a number of other methods for feature fusion, including model-, and late-fusion.

Take a look at these papers which might help you:

• Specific to a health-based application

• figure which might help you to grasp the concept