Many values in the dataset
The easiest thing to do is to jitter your data by adding 0.0001 * numpy.raodom.randn(*your array shape*) to your data. Whether it will help you in your specific problem, no one can tell, of course.
I have some questions about how to deal with 0 value in 2d array.
I am planning to work on regression 1d CNN, but most of the data is made of 0.
I would like to replace this 0 to other small values such as 0.000001 simply because, if I put 0, regression process would not take into account the dataset values and find what is optimized model for my data set.
I have some instinct but, I need to prove it by referencing.
Would you be kind enough as to recommend me some references or any idea of this?
Thank you for reading.