# GO语言利用K近邻算法实现小说鉴黄

Usuage:
go run kNN.go --file="data.txt"

`package main import ( "bufio" "flag" "fmt" "io" "log" "math" "os" "path" "path/filepath") var debug bool = falsevar data_dir string = "./moyan" //文件存放目录var limen float64 = 0.1159203888322267 //阈值 const ( MIN_HANZI rune = 0x3400 MAX_HANZI rune = 0x9fbb) var labels []rune = []rune{ 0x817f, 0x80f8, 0x4e73, 0x81c0, 0x5c41, 0x80a1, 0x88f8, 0x6deb,} func errHandle(err error) { if err != nil { log.Fatal(err) }} func load(name string) (m map[rune]int, err error) { f, err := os.Open(name) if err != nil { return nil, err } defer f.Close() buf := bufio.NewReader(f) m = make(map[rune]int) var r rune for { r, _, err = buf.ReadRune() if err != nil { if err == io.EOF { break } return nil, err } if r >= MIN_HANZI && r <= MAX_HANZI { m[r] += 1 } } return m, nil}func classify(m map[rune]int) (idv []float64, dis float64) { len_m := len(m) for i, v := range labels { if debug { fmt.Println(i, m[v], string(v), float64(m[v])/float64(len_m)) } idv = append(idv, float64(m[v])/float64(len_m)) } for _, v := range idv { dis += math.Pow(v, 2) } dis = math.Sqrt(dis) return}func check(fp string, dis float64) { switch { case dis >= limen: fmt.Println(fp, dis, "涉黄") case dis == 1.0: fmt.Println(fp, dis, "你在作弊吗") case dis == 0: fmt.Println(fp, dis, "检查一下文件字符编码是不是utf8格式吧") default: fmt.Println(fp, dis, "正常") }} func walkFunc(fp string, info os.FileInfo, err error) error { if path.Ext(fp) == ".txt" { m, err := load(fp) errHandle(err) _, dis := classify(m) check(fp, dis) } return err} var file string func init() { _, err := os.Stat(data_dir) if err != nil { err = os.Mkdir(data_dir, os.ModePerm) errHandle(err) } flag.StringVar(&file, "file", "", "file read in,if you don't give the file read in,"+ "it will create a data dictionary,just pust your files in it")} func main() { flag.Parse() if file == "" { filepath.Walk(data_dir, walkFunc) return } m, err := load(file) errHandle(err) _, dis := classify(m) check(file, dis) }`