https://github.com/n3integration/classifier

A general purpose text classifier
https://github.com/n3integration/classifier

classification k-nearest-neighbors machine-learning naive-bayes

Last synced: 3 months ago
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A general purpose text classifier

• Host: GitHub
• URL: https://github.com/n3integration/classifier
• Owner: n3integration
• License: apache-2.0
• Created: 2016-09-03T18:55:57.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2023-02-09T00:41:00.000Z (over 3 years ago)
• Last Synced: 2026-01-14T12:31:42.126Z (5 months ago)
• Topics: classification, k-nearest-neighbors, machine-learning, naive-bayes
• Language: Go
• Homepage:
• Size: 63.5 KB
• Stars: 43
• Watchers: 1
• Forks: 10
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# classifier

General purpose text classifier (naïve bayes, k-nearest neighbors)

[![codecov](https://codecov.io/gh/n3integration/classifier/branch/master/graph/badge.svg)](https://codecov.io/gh/n3integration/classifier)

[![Go Report Card](https://goreportcard.com/badge/github.com/n3integration/classifier)](https://goreportcard.com/report/github.com/n3integration/classifier)

[![Documentation](https://godoc.org/github.com/n3integration/classifier?status.svg)](http://godoc.org/github.com/n3integration/classifier)

## Installation

```bash

go get github.com/n3integration/classifier

```

## Usage

### Classification

There are two methods of classifying text data: `io.Reader` or `string`. To classify strings, use the `TrainString` 

or `ClassifyString` functions. To classify larger sources, use the `Train` and `Classify` functions that 

take an `io.Reader` as input.

```go

package main

import (

	"fmt"

	

	"github.com/n3integration/classifier/naive"

)

func main() {

    classifier := naive.New()

    classifier.TrainString("The quick brown fox jumped over the lazy dog", "ham")

    classifier.TrainString("Earn a degree online", "ham")

    classifier.TrainString("Earn cash quick online", "spam")

    

    if classification, err := classifier.ClassifyString("Earn your masters degree online"); err == nil {

        fmt.Println("Classification => ", classification) // ham

    } else {

        fmt.Println("error: ", err)

    }	

}

```

## Contributing

- Fork the repository

- Create a local feature branch

- Run `gofmt`

- Bump the `VERSION` file using [semantic versioning](https://semver.org/)

- Submit a pull request

## License

Copyright 2023 n3integration@gmail.com

Licensed under the Apache License, Version 2.0 (the "License");

you may not use this file except in compliance with the License.

You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

distributed under the License is distributed on an "AS IS" BASIS,

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and

limitations under the License.