Apr-29-2020, 11:58 AM
Hi!
I have a big medical database(.csv) with apr. 15 variable. All variables can be non-measured, normal, or abnormal. A row shows a patient's measures, usually not a lot of the 15 things (Iron, CRP, Albumin...) are measured.
My task would be to find the dependencies between the variables. As far I know it is called Bayesian Network, but not sure. I need the DAG (directed acyclic graph) to visualize the dependencies. Do you know how should I do this? I've been looking for tutorials or anyone who has ever done this but nothing so far.
The easiest way to use Python libraries I guess.
Ty for help
I have a big medical database(.csv) with apr. 15 variable. All variables can be non-measured, normal, or abnormal. A row shows a patient's measures, usually not a lot of the 15 things (Iron, CRP, Albumin...) are measured.
My task would be to find the dependencies between the variables. As far I know it is called Bayesian Network, but not sure. I need the DAG (directed acyclic graph) to visualize the dependencies. Do you know how should I do this? I've been looking for tutorials or anyone who has ever done this but nothing so far.
The easiest way to use Python libraries I guess.
Ty for help