Hi mixOmics team,

Thanks for a great package. I’m aiming to use it for neuroimaging analysis and have had success with the DIABLO function.

I was wondering if there’s a tune.block.spls function/workaround/equivalent to tune keepX. I can’t seem to find anything specific, nor in the generic tune function. Apologies if I’ve missed something obvious.

Thank you,

hi @djaka,

Unfortunately we have no tuning function (and very few or no performance measures) for that module so far. We are about to launch a tune.spls() as a first step towards this, but it will be a long way before we reach the multi block. You can use a more exploratory analysis rather than having to rely on an ‘optimal’ keepX.


Thanks Kim-Anh.

I’ve put together a brief function which conceptually is the same as tune.spls (i.e. repeated M-fold cross validation and use the lowest MSE value to select optimal values), however looped this over all combination of KeepX for blocks. I believe this is was tune.block.splsda does. Luckily I’m only interested in 1 component.

Conceptually, can I check if there’s any reason this wouldn’t be valid?

Thanks again,

Dear @djaka,

Given that you are (I assume) only dealing with one y response, I think it should be fine, as this would be a similar case as tune.block.splsda but for a continuous y variable. The reason why we are still struggling with a tuning function is that we consider Y with multiple response variables.

Good luck in your analyses,