1 files changed, 0 insertions, 48 deletions
diff --git a/BNW_parameter_learning/parameterLearning.m b/BNW_parameter_learning/parameterLearning.m
deleted file mode 100644
index 414ffe6c..00000000
--- a/BNW_parameter_learning/parameterLearning.m
+++ /dev/null
@@ -1,48 +0,0 @@
-function [ bnet ] = parameterLearning( bnet,cases,engine_name )
-%parameterLearning Do parameter learning and inference
-% It returns the bnet with parameters learned from the data in cases.
-% 
-% This is very basic now. It could be modified to use different engine
-%  types in the future. Now, I always use the 'jtree_inf_engine'.
-% 
-%
-% parameterLearning is called by runBN_initial.m, 
-%   Predictmultiple.m, and Predictmultipleintervention.m
-
-
-%engine is an optional argument
-if nargin < 3
-    engine_name = 'jtree_inf_engine';
-end
-
-
-%First do parameter learning with all the data
-[bnet] = getParams(bnet,cases);
-
-
-
-
-end
-
-function [ bnet ] = getParams( bnet, cases )
-%getParams Code to initialize CPT and do parameter learning.
-%This will be very basic for now.  I can add more options later.
-%
-
-dnodes = bnet.dnodes;
-cnodes = bnet.cnodes;
-nnodes = size(dnodes,2)+size(cnodes,2);
-
-%make dnodes tabular_CPT
-for i = 1:size(dnodes,2)
-    bnet.CPD{dnodes(i)} = tabular_CPD(bnet,dnodes(i));
-end
-
-for i = 1:size(cnodes,2)
-    bnet.CPD{cnodes(i)} = gaussian_CPD(bnet,cnodes(i));
-end
-
-bnet = learn_params(bnet,cases);
-
-
-end