Spam classifier in Go using Naive Bayes

In plain words

This is a spam classification tool built in Go that uses Naive Bayes machine learning to identify unwanted messages. It's designed for developers who need to filter spam from legitimate content in their applications. The project provides a straightforward implementation of the Naive Bayes algorithm, making it suitable for those building email systems, chat applications, or other platforms requiring automated message filtering.

written from the facts on this page · September 2026

From the sources

A Naive Bayes spam classifier implementation in Go, enabling text classification system using the Naive Bayes algorithm with Laplace smoothing to classify messages as spam or not spam. go get github.com/igomez10/nspammer Usage Basic Example package main import ( "fmt" "github.com/igomez10/nspammer" ) func main () { // Create training dataset (map[string]bool where true = spam, false = not spam) trainingData := map [ string ] bool { "buy viagra now" : true , "get rich quick" : true , "meeting at 3pm" : false , "project update report" : false , } // Create and train classifier classifier := nspammer . NewSpamClassifier ( trainingData ) // Classify new messages isSpam := classifier . Classify…from github.com

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