**140**wrote:

Hi All,

PCA for 3 dimensional matrices, I have 3 matrices (A (contains drugs), B(contains diseases), and C(contains Pathways)). Out of which Matrix A has 86 columns, matrix B has 177 columns and Matrix C has 877 columns(or features). Now I want to do some kind of feature selection using PCA which can reduce the features of C in combination with matrix A and B.

Can someone suggest me some ideas to perform such analyses? I have the PCA algorithm, but I actually want to understand how can I input such matrices to get the potential features from C affecting combination of A and B.

Thanks,

**23k**• written 5.2 years ago by pbio •

**140**

PCA only really makes sense on a single matrix. I assume you have the same number of rows for all of these matrices, so you could just merge them all together into a larger matrix and run the PCA on that. Personally I'd use something more traditional for feature selection like a random forest.

97kExactly... this is what I was thinking.. thanks...

140