https://github.com/somdipdey/markovian_csharp

Markov Model (N characters) library written in CSharp C#
https://github.com/somdipdey/markovian_csharp

csharp markov markov-model text-generation

Last synced: 6 months ago
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Markov Model (N characters) library written in CSharp C#

• Host: GitHub
• URL: https://github.com/somdipdey/markovian_csharp
• Owner: somdipdey
• Created: 2018-01-19T23:33:49.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-01-20T15:56:41.000Z (over 7 years ago)
• Last Synced: 2025-02-15T10:31:17.818Z (8 months ago)
• Topics: csharp, markov, markov-model, text-generation
• Language: C#
• Size: 26.4 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Markovian_CSharp

Markov Model (N characters + N words) library written in CSharp [C#]. MarkovModel class provides the wrapper for Markov Model for N Characters, whereas, MarkovWordModel class provides wrapper for Markov Model for N words.

[![Build Status](https://travis-ci.org/somdipdey/Markovian_CSharp.svg?branch=master)](https://travis-ci.org/somdipdey/Markovian_CSharp)

## Using Markov Model in C#

#### MarkovModel for characters in use:

            // Training text in string format

            String st = "I completed Hack Reactor in July 2016 and took almost 3 months before accepting an offer with Radius Intelligence.\n"+

                " I applied to 291 companies, did 32 phone screens, 16 technical screens, 13 coding challenges, 11 on-sites, and received 8 offers.\n" +

                "The offers ranged from $60-125k in salary from companies all over the US, and for both front end and full stack roles. In total, 2.8% of applications became offers.\n" + 

                "Here are 5 things I wish I’d known before I began my job search.";

            // Replace any new line with blank spaces to generate random text

            st = st.Replace('\n', ' ');

            // Create a new MarkovModel object, initialized with a keyLength of 6

            MarkovModel markov = new MarkovModel(6);

            // Train Markov model with the input text

            markov.SetTraining(st);

            // Set the seed of the random number generator

            markov.SetRandom(1);

            // Print out four random texts

            for (int k = 0; k < 4; k++)

            {

                String text = markov.GetRandomText(500);

                Console.Write(text + Environment.NewLine);

            }

            

            //Output::

            /*

            I applied to 291 companies, did 32 phone screens, 13 coding challenges, 11 on-sites, and received 8 offer with Radius Intelligence.  I applied to 291 companies, did 32 phone screens, 16 technical screens, 16 technical screens, 16 technical screens, 16 technical screens, 16 technical screens, 16 technical screens, 16 technical screens, 13 coding challenges, 11 on-sites, and for both front end and full stack roles. In total, 2.8% of applications became offers. Here are 5 things I wish I’d known be

            ons became offer with Radius Intelligence.  I applications became offers ranged from companies, did 32 phone screens, 13 coding challenges, 11 on-sites, and received 8 offer with Radius Intelligence.  I applications became offers. The offers ranged from companies all over the US, and for both front end and for both front end and for both front end and full stack roles. In total, 2.8% of applied to 291 companies, did 32 phone screens, 16 technical screens, 13 coding challenges, 11 on-sites, and r

            ted Hack Reactor in July 2016 and took almost 3 months before accepting an offer with Radius Intelligence.  I applications became offers. Here are 5 things I wish I’d known before I began my job search.

            st 3 months before I began my job search.

            */

#### Markov Model for words in use:

            // Initialise Markov Model for Words

            MarkovWordModel markovWord = new MarkovWordModel(4);

            // Set the training text without any new line in it. 

            markovWord.SetTraining(st);

            // Set the seed

            markovWord.SetRandom(10);

            // Printout random words

            Console.Write(markovWord.GetRandomText(200) + Environment.NewLine);