The ndarray (6,3,3) => (row, col,color channels) I tried fixing it converting the list of numpy.ndarray to numpy.asarray(list)
but this causes a different problem: is grid use a lot a memory.. I am running on a super computer, and seem to have problems with memory.. already used 62 gb ram.. > Den 16. mar. 2017 kl. 05.30 skrev Sebastian Raschka <se.rasc...@gmail.com>: > > Sklearn estimators typically assume 2d inputs (as numpy arrays) with > shape=[n_samples, n_features]. > >> list of Np.ndarrays of shape (6,3,3) > > I assume you mean a 3D tensor (3D numpy array) with shape=[n_samples, > n_pixels, n_pixels]? What you could do is to reshape it before you put it in, > i.e., > > data_ary = your_ary.reshape(n_samples, -1).shape > > then, you need to add a line at the beginning your CNN class that does the > reverse, i.e., data_ary.reshape(6, n_pixels, n_pixels).shape. Numpy’s reshape > typically returns view objects, so that these additional steps shouldn’t be > “too” expensive. > > Best, > Sebastian > > > >> On Mar 16, 2017, at 12:00 AM, Carlton Banks <nofl...@gmail.com> wrote: >> >> Hi… >> >> I currently trying to optimize my CNN model using gridsearchCV, but seem to >> have some problems feading my input data.. >> >> My training data is stored as a list of Np.ndarrays of shape (6,3,3) and my >> output is stored as a list of np.array with one entry. >> >> Why am I having problems parsing my data to it? >> >> best regards >> Carl B. >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
