asha24choudhary

Hi @amit-sharma. Was thinking if we should introduce feature lags as new features to deal with time series data. What I mean is if we have feature A,B, C, do...

Or was wondering should we use a model in the model parameter which takes into account temporal dependencies?

Oh thank you :)

I am facing the same problem, have gpu with 8 cores. """ Number of devices: 8 -- Kernel partition size: 0 Number of devices: 8 -- Kernel partition size: 42625...

do u think if it was a good idea to calculate [pseudo inverse](https://numpy.org/doc/stable/reference/generated/numpy.linalg.pinv.html), if the inverse of the sub_corr_matrix gives error?

i understood how you did it, but do u have a method which generates the graph rom the adjacency matrix?

I further investigated in the final graph **G** that I got from FCI. ``` a=[] for i in range(len(nodes_forbidden)): if (G.get_directed_edge(nodes[nodes_forbidden[i][0]], nodes[nodes_forbidden[i][1]])) is not None: print(nodes_forbidden[i]) a.append(nodes_forbidden[i]) ``` Length of...