classifier

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

Installation

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.

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
Submit a pull request

License

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.