General purpose text classifier (naïve bayes, k-nearest neighbors)
go get github.com/n3integration/classifierThere 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)
}
}- Fork the repository
- Create a local feature branch
- Run
gofmt - Bump the
VERSIONfile using semantic versioning - Submit a pull request
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.