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https://github.com/mb-14/gomarkov

Markov chains in golang
https://github.com/mb-14/gomarkov

golang markov-chain nlp

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Markov chains in golang

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# gomarkov
[![GoDoc](https://godoc.org/github.com/mb-14/gomarkov?status.svg)](https://godoc.org/github.com/mb-14/gomarkov)
[![Go Report Card](https://goreportcard.com/badge/github.com/mb-14/gomarkov)](https://goreportcard.com/report/github.com/mb-14/gomarkov)

Go implementation of markov chains for textual data.

You can find out more about markov chains [here](http://setosa.io/ev/markov-chains/) and [here](https://towardsdatascience.com/introduction-to-markov-chains-50da3645a50d)

## Usage
```go
package main

import (
"github.com/mb-14/gomarkov"
"fmt"
"strings"
"io/ioutil"
"encoding/json"
)

func main() {
//Create a chain of order 2
chain := gomarkov.NewChain(2)

//Feed in training data
chain.Add(strings.Split("I want a cheese burger", " "))
chain.Add(strings.Split("I want a chilled sprite", " "))
chain.Add(strings.Split("I want to go to the movies", " "))

//Get transition probability of a sequence
prob, _ := chain.TransitionProbability("a", []string{"I", "want"})
fmt.Println(prob)
//Output: 0.6666666666666666

//You can even generate new text based on an initial seed
chain.Add(strings.Split("Mother should I build the wall?", " "))
chain.Add(strings.Split("Mother should I run for President?", " "))
chain.Add(strings.Split("Mother should I trust the government?", " "))
next, _ := chain.Generate([]string{"should", "I"})
fmt.Println(next)

//The chain is JSON serializable
jsonObj, _ := json.Marshal(chain)
err := ioutil.WriteFile("model.json", jsonObj, 0644)
if err != nil {
fmt.Println(err)
}
}
```
## Examples

- [Gibberish username detector](/examples/gibberish)

- [Fake Hackernews post generator](/examples/fakernews)

- [Pokemon name generator](/examples/pokenamer)