is there any way to use both Spearman and Euclidean distance using knnsearch ?
1 visualizzazione (ultimi 30 giorni)
Mostra commenti meno recenti
zakaria debih
il 21 Mag 2019
Risposto: zakaria debih
il 22 Mag 2019
in my programe I'm using them separatly as in the text below :
%% Distance effect
idx=knnsearch(subject_train,subject_test,'distance','Euclidean');
%idx=knnsearch(subject_train,subject_test,'distance','spearman');
I assume that there is a way to merge the two functions to get better results, I expect that one of them can compensate the bad results of the other one
0 Commenti
Risposta accettata
the cyclist
il 21 Mag 2019
No, they cannot both be used within a single call to knnsearch.
I don't really see how "merging" would really be that helpful. It seems to me that that would be effectively equivalent to defining some new, different distance metric. If one of the tried and tested distance functions doesn't really do a good job, I don't think a newfangled one will do much better.
You could, in principle, create your own version of knnsearch that does that merging, by copying the built-in function into your own directory, calculating both distances inside your new function, and somehow do the "merging" you have in mind.
0 Commenti
Più risposte (1)
Vedere anche
Categorie
Scopri di più su Dimensionality Reduction and Feature Extraction in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!