Hi dear all, I recently tested MKLRegression with a dataset containing 750 vector samples of 1.3million dense dimensions. It takes about 24hours for training in our cluster. Nevertheless, The training uniquely seems to work for the PolyKernel. For other kernels the machine does not learn, i.e. predicted output for the test set is a constant (all predicted values are equal, near to the mean of the real relationship values, see Figure attached for 50 samples).
What do you suggest me for tracking the problem? In this case, in order to you reproduce the issue, I think it is needed you have my dataset (or probably any other with similar characteristics). Thank you. -- *Ignacio Arroyo-Fernández*
