please some one explain the 1d CNN layers and how to prepare your data of size 2968 row and 101 column to pass into the CNN layers, the last column is the target column and the first hundred are input data.
If you want to regress the last column from a 100-long time series, this is how you could write your dataset:
class CustomDataset(torch.utils.data.Dataset): def __init__(self, data): self.x = data[:,:-1] self.y = data[:,-1] def __getitem__(self, index): return (self.x[index,:], self.y[index]) def __len__(self): return self.x.size()
You can then access your data using either the naive
for x,y in MyDataset: approach, or use a dataloader.
For more details on the Conv1D, you can refer to this post here