I have a dataset of 1000 tumours described by 6 parameters (my independent variables). For each tumour I have a value of the accuracy of 8 different segmentation methods.
I would like to build a model that can predict, given the 6 parameters describing a tumour, which segmentation method would yield the highest accuracy score. Is there any way I can do this with a decision tree, or even random forest approach? If so, is there any software that can do that ? (SPSS seems to only deal with binary decision trees) And if not, do you have a different suggestion?