My data looks like this (F=Features)
F1 F2 F3 F4 F5 F6 F7 F8....
ID1 0.67 0.76 0.3 0.54 0.21 0.88 0.97 0.45....
ID2 0.76 0.68 0.10 0.45 0.12 0.44 0.79 0.54....
ID3 0.67 0.76 0.3 0.54 0.21 0.88 0.68 0.76....
ID4 0.67 0.10 0.3 0.45 0.3 0.88 0.97 0.45....
...
...
...
I have about 40 features (I have just put 8 here). If I set a threshold for, say 4 features, what I am looking for is a combination of 4 features which, together, are most relevant and significant in the dataset. I need some kind of score that measures how good a combination of features is. This is what I meant by the confidence score (or whatever score we may call it). So instead of selecting 1 feature I want to select a combination of 4 features. For example.
F1-F4-F9-F12 = 0.92
F2-F3-F7-F6 = 0.85
F5-F3-F4-F8 = 0.667
Here, F1-F4 is not subtraction. I am just attaching the two features together. The scores above, I do not know how to get it. That is my question? So I do not know what kind of a test to use or can be used.
How can I go about it? Thanks
feature-selection
tag, but what are those features?) $\endgroup$F5-F3 = 0.667
, could you explain this? $\endgroup$