MATLAB Answers

Bayesian Network K2 algorithm to find maximum likelihood.

10 views (last 30 days)
Ashwani Kumar MAlviya
Ashwani Kumar MAlviya on 11 Nov 2020
Hii All
I am using K2 algorithm of Bayesian Network praposed by Cooper and Harkovitz (1992).
I found the codes developed by Guangdi Li for learning DAG structure.
The code is running perfect (thanks to Li). I have to make little adjustments according to my requirment.
So, here is the issue.
The code suggested by Li is below.
clear all
clc
% data = csvread ('UC1_FGC_Women_zeros.csv');
% save ('Sample_1.mat', 'data')
% ControlCentor
% when you test the code, please correct the directory in next command
load ( 'C: \ Users \ ashwa \ Desktop \ aitec \ Work \ DIAMOND \ Task-2 \ MATLAB for Bayes \ K2 \ Sample_1.mat' );
% Sample is a variable that saves our training database.
LGObj = ConstructLGObj (Sample_1); % construct an object
% Order = [3 4 1 2 5 8 7 10 9 6]; % Order is the ordering of the input in K2 algorithm
Order = 1: 143;
u = 20; % u is the maximum edges of node in output graph.
[DAG, K2Score] = k2 (LGObj, Order, u);
h = view (biograph (DAG));
I have to make adjustmet for the "Order". I need that order must be generated randomly and perform 5000 iteration and then search the maximum liklyhood network from those 5000 iterations
So, to randomize the order, i have written
Order = reshape (randperm (LGObj.VarNumber), 1, length (randperm (LGObj.VarNumber)));
. It is working fine. No issues here. If I repalce the order in Li's code with this one, I will get a graph with randomly generated order.
Now I want to repeat this process altleast 5000 times and I need my output as a DAG matrix which have maximum sum (K2Score).
Thank you very much in advance.
Regards
Ashwani

Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by