Create and Populate an Internal Data Structure of the PGM - IT/Computer Science Assignment Help

Assignment Task:

Task:

1. Introduction 
This assignment has two parts: Probability Graph Model (Section 2) and Part-of-Speech Tagging (Section 3). Both UG and PG students need to finish both parts. In part one, you are expected to perform approximate inference on a given PGM using C++/Java/Python and submit the codes to the Web Submission system. In part two, you are expected to provide your work for the required computation in a pdf and submit the pdf in MyUni, Assignment 3. 
2. Probability Graph Model (10 marks) 
Your task is to perform approximate inference on a probabilistic graphical model (PGM) of Boolean random variables using likelihood weighted sampling, as described in lecture. You will work on two networks (Burglar and Fire). The networks and example queries are provided in the textual files attached on MyUni and will be described in the later section. 
2.1 The task 
You need to write a program (C++/Java/Python) to parse the input file of network and to create and populate an internal data structure of the PGM. The program also need to parse the input query file correctly and evaluate the conditional probability distribution of the query variable, given the evidence. The result must be written as two decimal values corresponding to the values of P(QueryVar=true I...) and P(QueryVar=false I ...) onto the standard output stream, separated by white space. For example: 
0.872 0.128 
Note that if you write anything else before these two numbers, automark will interpret that output as the answer, almost certainly resulting in a test failure. 
2.2 File Format 
The format of the network file is: 

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