I am trying to follow this example posted on git.
I want to modify the example and use data I have downloaded(wisconsin breast cancer dataset). I have it all transferred from csv to hdf5 file.
It is not clear to me how am I suppose to input this data to the network?
It consists of 700 rows and 11 columns which 1 of the columns is the 'label' column for prediction.
To my understanding each row should be inputed independently to other rows for correct training?
Thanks in advance
Please see this answer on how to prepare HDF5 data for caffe's
"HDF5Data"input layer.Basically, you need to have two "datasets" inside the hdf5 file: one for the inputs and one for the label. Each dataset is a multi-dimensional array with the first dimension being the "batch" dimension. In your example, you have 700 examples of dimension 10 as input and 700 labels of dimension 1.