Home » Machine Learning/Artificial Intelligence

# Markov Random Field Model in Machine Learning

In the previous article we have learnt about directed graph model called Bayesian graphical Model. Now, in this article we are going to discuss about **undirected graph model called Markov's random field model**.

Submitted by Bharti Parmar, on March 24, 2019

## Markov's Random Fields

**Markov random model** is a model which use an undirected graph. Undirected graphical models edge represents the potential between two variables, syntactically, Factorization distribution probabilities between variable. In each Individual variable connected with the edge represent a certain clique in the graph; means probability distribution of the variables in the graph can factorize an individual clique potential function.

Just as we had CPDs for Bayesian networks, we have tables to incorporate relations between nodes in **Markov networks**. However, there are two crucial differences between these tables and CPDs.

**Clique** in graph theory.it is a subset of vertices of an undirected graph.

**P(A, B, C, D, E) α Ф(A,B) Ф (B,C) Ф (B,D) Ф (C,E) Ф (D,E)**

**Such that:** It induces sub graph is complete in every vertices in a clique is adjacent. So, clique in this graph adjust adjacently one by one.

**Like,**

It is some different if we join **D,C** and **B,E** clique over here then it is also change its probability.

**P(A, B, C, D, E) α Ф(A,B) Ф (B,C,D) Ф (C,D,E)**

Some undirected graphic model has Markov Random Field. In MRF certain paths between **A** and **C**.

A -> B -> C A -> B -> D -> E -> C

**Note that:** Markov networks do not need to be acyclic, as was the case with Bayesian networks.

**Independence properties such as Markov properties:**

- Any 2 subsets if variables are conditionally independent given a separating subset.
- If we take
**'A'**as a subset and**'C'**as one subset then there is wore between them. So, there is no way to go between**'A'**and**'C'**without getting threw the subset. So, we are using**(A, B)**than**B, C, D, E**.

**Therefore**, A and C are separating subsets

- Any 2 subset of variable are conditionally independent given a separating subset.
- {B,D}, {B,E} and {B,D,E} are separating subsets.

**Conclusion:** In this article we will learn about **Markov Random Field model**, its potential function and its properties.

**Reference:** Probabilistic Graphical Models Tutorial — Part 1

What's New

- C Language MCQs
- Python MCQs
- Perl MCQs
- MongoDB MCQs
- Java MCQs
- C# MCQs
- Scala MCQs
- Blockchain MCQs
- AutoCAD MCQs
- PHP MCQs
- JavaScript MCQs
- jQuery MCQs
- ReactJS MCQs
- AngularJS MCQs
- JSON MCQs
- Ajax MCQs
- SASS MCQs
- HTML MCQs
- Advanced CSS MCQs
- CSS MCQs
- OOPs MCQs
- PL/SQL MCQs
- SQL MCQs
- Oracle MCQs
- SQLite MCQs
- MS Word MCQs
- Software Engineering MCQs
- Operating System MCQs
- Project Management MCQs
- Data Analytics and Visualization MCQs
- MIS MCQs
- Linux MCQs
- WordPress MCQs
- Blogging MCQs
- Marketing MCQs

- Generally Accepted Accounting Principles MCQs
- Bills of Exchange MCQs
- Business Environment MCQs
- Sustainable Development MCQs
- Marginal Costing and Absorption Costing MCQs
- Globalisation MCQs
- Indian Economy MCQs
- Retained Earnings MCQs
- Depreciation MCQs
- Partnership MCQs
- Sole Proprietorship MCQs
- Goods and Services Tax (GST) MCQs
- Cooperative Society MCQs
- Capital Market MCQs
- Business Studies MCQs
- Basic Accounting MCQs
- MIS Executive Interview Questions
- Go Language Interview Questions

Top Interview Coding Problems/Challenges!

- Run-length encoding (find/print frequency of letters in a string)
- Sort an array of 0's, 1's and 2's in linear time complexity
- Checking Anagrams (check whether two string is anagrams or not)
- Relative sorting algorithm
- Finding subarray with given sum
- Find the level in a binary tree with given sum K
- Check whether a Binary Tree is BST (Binary Search Tree) or not
- 1[0]1 Pattern Count
- Capitalize first and last letter of each word in a line
- Print vertical sum of a binary tree
- Print Boundary Sum of a Binary Tree
- Reverse a single linked list
- Greedy Strategy to solve major algorithm problems
- Job sequencing problem
- Root to leaf Path Sum
- Exit Point in a Matrix
- Find length of loop in a linked list
- Toppers of Class
- Print All Nodes that don't have Sibling
- Transform to Sum Tree
- Shortest Source to Destination Path

Comments and Discussions!