mirror of
https://github.com/mjl-/mox.git
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440 lines
12 KiB
Go
440 lines
12 KiB
Go
package main
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/*
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note: these testdata paths are not in the repo, you should gather some of your
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own ham/spam emails.
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./mox junk train testdata/train/ham testdata/train/spam
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./mox junk train -sent-dir testdata/sent testdata/train/ham testdata/train/spam
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./mox junk check 'testdata/check/ham/mail1'
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./mox junk test testdata/check/ham testdata/check/spam
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./mox junk analyze testdata/train/ham testdata/train/spam
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./mox junk analyze -top-words 10 -train-ratio 0.5 -spam-threshold 0.85 -max-power 0.01 -sent-dir testdata/sent testdata/train/ham testdata/train/spam
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./mox junk play -top-words 10 -train-ratio 0.5 -spam-threshold 0.85 -max-power 0.01 -sent-dir testdata/sent testdata/train/ham testdata/train/spam
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*/
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import (
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"flag"
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"fmt"
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"log"
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mathrand "math/rand"
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"os"
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"runtime"
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"runtime/pprof"
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"sort"
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"time"
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"github.com/mjl-/mox/junk"
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"github.com/mjl-/mox/message"
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"github.com/mjl-/mox/mlog"
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"github.com/mjl-/mox/mox-"
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)
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type junkArgs struct {
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params junk.Params
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cpuprofile, memprofile string
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spamThreshold float64
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trainRatio float64
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seed bool
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sentDir string
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databasePath, bloomfilterPath string
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debug bool
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}
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func (a junkArgs) Memprofile() {
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if a.memprofile == "" {
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return
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}
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f, err := os.Create(a.memprofile)
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xcheckf(err, "creating memory profile")
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defer f.Close()
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runtime.GC() // get up-to-date statistics
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err = pprof.WriteHeapProfile(f)
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xcheckf(err, "writing memory profile")
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}
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func (a junkArgs) Profile() func() {
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if a.cpuprofile == "" {
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return func() {
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a.Memprofile()
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}
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}
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f, err := os.Create(a.cpuprofile)
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xcheckf(err, "creating CPU profile")
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err = pprof.StartCPUProfile(f)
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xcheckf(err, "start CPU profile")
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return func() {
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pprof.StopCPUProfile()
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f.Close()
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a.Memprofile()
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}
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}
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func (a junkArgs) SetLogLevel() {
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mox.Conf.Log[""] = mlog.LevelInfo
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if a.debug {
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mox.Conf.Log[""] = mlog.LevelDebug
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}
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mlog.SetConfig(mox.Conf.Log)
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}
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func junkFlags(fs *flag.FlagSet) (a junkArgs) {
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fs.BoolVar(&a.params.Onegrams, "one-grams", false, "use 1-grams, i.e. single words, for scoring")
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fs.BoolVar(&a.params.Twograms, "two-grams", true, "use 2-grams, i.e. word pairs, for scoring")
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fs.BoolVar(&a.params.Threegrams, "three-grams", false, "use 3-grams, i.e. word triplets, for scoring")
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fs.Float64Var(&a.params.MaxPower, "max-power", 0.05, "maximum word power, e.g. min 0.05/max 0.95")
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fs.Float64Var(&a.params.IgnoreWords, "ignore-words", 0.1, "ignore words with ham/spaminess within this distance from 0.5")
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fs.IntVar(&a.params.TopWords, "top-words", 10, "number of top spam and number of top ham words from email to use")
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fs.IntVar(&a.params.RareWords, "rare-words", 1, "words are rare if encountered this number during training, and skipped for scoring")
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fs.BoolVar(&a.debug, "debug", false, "print debug logging when calculating spam probability")
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fs.Float64Var(&a.spamThreshold, "spam-threshold", 0.95, "probability where message is seen as spam")
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fs.Float64Var(&a.trainRatio, "train-ratio", 0.5, "part of data to use for training versus analyzing (for analyze only)")
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fs.StringVar(&a.sentDir, "sent-dir", "", "directory with sent mails, for training")
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fs.BoolVar(&a.seed, "seed", false, "seed prng before analysis")
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fs.StringVar(&a.databasePath, "dbpath", "filter.db", "database file for ham/spam words")
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fs.StringVar(&a.bloomfilterPath, "bloompath", "filter.bloom", "bloom filter for ignoring unique strings")
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fs.StringVar(&a.cpuprofile, "cpuprof", "", "store cpu profile to file")
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fs.StringVar(&a.memprofile, "memprof", "", "store mem profile to file")
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return
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}
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func listDir(dir string) (l []string) {
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files, err := os.ReadDir(dir)
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xcheckf(err, "listing directory %q", dir)
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for _, f := range files {
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l = append(l, f.Name())
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}
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return l
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}
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func must(f *junk.Filter, err error) *junk.Filter {
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xcheckf(err, "filter")
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return f
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}
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func cmdJunkTrain(c *cmd) {
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c.unlisted = true
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c.params = "hamdir spamdir"
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c.help = "Train a junk filter with messages from hamdir and spamdir."
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a := junkFlags(c.flag)
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args := c.Parse()
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if len(args) != 2 {
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c.Usage()
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}
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defer a.Profile()()
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a.SetLogLevel()
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f := must(junk.NewFilter(mlog.New("junktrain"), a.params, a.databasePath, a.bloomfilterPath))
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defer f.Close()
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hamFiles := listDir(args[0])
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spamFiles := listDir(args[1])
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var sentFiles []string
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if a.sentDir != "" {
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sentFiles = listDir(a.sentDir)
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}
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err := f.TrainDirs(args[0], a.sentDir, args[1], hamFiles, sentFiles, spamFiles)
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xcheckf(err, "train")
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}
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func cmdJunkCheck(c *cmd) {
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c.unlisted = true
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c.params = "mailfile"
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c.help = "Check an email message against a junk filter, printing the probability of spam on a scale from 0 to 1."
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a := junkFlags(c.flag)
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args := c.Parse()
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if len(args) != 1 {
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c.Usage()
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}
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defer a.Profile()()
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a.SetLogLevel()
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f := must(junk.OpenFilter(mlog.New("junkcheck"), a.params, a.databasePath, a.bloomfilterPath, false))
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defer f.Close()
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prob, _, _, _, err := f.ClassifyMessagePath(args[0])
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xcheckf(err, "testing mail")
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fmt.Printf("%.6f\n", prob)
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}
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func cmdJunkTest(c *cmd) {
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c.unlisted = true
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c.params = "hamdir spamdir"
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c.help = "Check a directory with hams and one with spams against the junk filter, and report the success ratio."
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a := junkFlags(c.flag)
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args := c.Parse()
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if len(args) != 2 {
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c.Usage()
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}
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defer a.Profile()()
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a.SetLogLevel()
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f := must(junk.OpenFilter(mlog.New("junktest"), a.params, a.databasePath, a.bloomfilterPath, false))
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defer f.Close()
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testDir := func(dir string, ham bool) (int, int) {
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ok, bad := 0, 0
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files, err := os.ReadDir(dir)
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xcheckf(err, "readdir %q", dir)
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for _, fi := range files {
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path := dir + "/" + fi.Name()
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prob, _, _, _, err := f.ClassifyMessagePath(path)
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if err != nil {
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log.Printf("classify message %q: %s", path, err)
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continue
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}
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if ham && prob < a.spamThreshold || !ham && prob > a.spamThreshold {
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ok++
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} else {
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bad++
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}
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if ham && prob > a.spamThreshold {
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fmt.Printf("ham %q: %.4f\n", path, prob)
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}
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if !ham && prob < a.spamThreshold {
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fmt.Printf("spam %q: %.4f\n", path, prob)
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}
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}
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return ok, bad
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}
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nhamok, nhambad := testDir(args[0], true)
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nspamok, nspambad := testDir(args[1], false)
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fmt.Printf("total ham, ok %d, bad %d\n", nhamok, nhambad)
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fmt.Printf("total spam, ok %d, bad %d\n", nspamok, nspambad)
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fmt.Printf("specifity (true negatives, hams identified): %.6f\n", float64(nhamok)/(float64(nhamok+nhambad)))
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fmt.Printf("sensitivity (true positives, spams identified): %.6f\n", float64(nspamok)/(float64(nspamok+nspambad)))
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fmt.Printf("accuracy: %.6f\n", float64(nhamok+nspamok)/float64(nhamok+nhambad+nspamok+nspambad))
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}
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func cmdJunkAnalyze(c *cmd) {
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c.unlisted = true
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c.params = "hamdir spamdir"
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c.help = `Analyze a directory with ham messages and one with spam messages.
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A part of the messages is used for training, and remaining for testing. The
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messages are shuffled, with optional random seed.`
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a := junkFlags(c.flag)
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args := c.Parse()
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if len(args) != 2 {
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c.Usage()
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}
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defer a.Profile()()
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a.SetLogLevel()
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f := must(junk.NewFilter(mlog.New("junkanalyze"), a.params, a.databasePath, a.bloomfilterPath))
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defer f.Close()
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hamDir := args[0]
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spamDir := args[1]
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hamFiles := listDir(hamDir)
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spamFiles := listDir(spamDir)
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var rand *mathrand.Rand
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if a.seed {
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rand = mathrand.New(mathrand.NewSource(time.Now().UnixMilli()))
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} else {
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rand = mathrand.New(mathrand.NewSource(0))
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}
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shuffle := func(l []string) {
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count := len(l)
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for i := range l {
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n := rand.Intn(count)
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l[i], l[n] = l[n], l[i]
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}
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}
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shuffle(hamFiles)
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shuffle(spamFiles)
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ntrainham := int(a.trainRatio * float64(len(hamFiles)))
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ntrainspam := int(a.trainRatio * float64(len(spamFiles)))
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trainHam := hamFiles[:ntrainham]
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trainSpam := spamFiles[:ntrainspam]
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testHam := hamFiles[ntrainham:]
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testSpam := spamFiles[ntrainspam:]
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var trainSent []string
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if a.sentDir != "" {
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trainSent = listDir(a.sentDir)
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}
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err := f.TrainDirs(hamDir, a.sentDir, spamDir, trainHam, trainSent, trainSpam)
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xcheckf(err, "train")
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testDir := func(dir string, files []string, ham bool) (ok, bad, malformed int) {
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for _, name := range files {
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path := dir + "/" + name
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prob, _, _, _, err := f.ClassifyMessagePath(path)
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if err != nil {
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// log.Infof("%s: %s", path, err)
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malformed++
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continue
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}
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if ham && prob < a.spamThreshold || !ham && prob > a.spamThreshold {
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ok++
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} else {
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bad++
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}
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if ham && prob > a.spamThreshold {
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fmt.Printf("ham %q: %.4f\n", path, prob)
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}
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if !ham && prob < a.spamThreshold {
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fmt.Printf("spam %q: %.4f\n", path, prob)
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}
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}
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return
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}
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nhamok, nhambad, nmalformedham := testDir(args[0], testHam, true)
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nspamok, nspambad, nmalformedspam := testDir(args[1], testSpam, false)
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fmt.Printf("training done, nham %d, nsent %d, nspam %d\n", ntrainham, len(trainSent), ntrainspam)
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fmt.Printf("total ham, ok %d, bad %d, malformed %d\n", nhamok, nhambad, nmalformedham)
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fmt.Printf("total spam, ok %d, bad %d, malformed %d\n", nspamok, nspambad, nmalformedspam)
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fmt.Printf("specifity (true negatives, hams identified): %.6f\n", float64(nhamok)/(float64(nhamok+nhambad)))
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fmt.Printf("sensitivity (true positives, spams identified): %.6f\n", float64(nspamok)/(float64(nspamok+nspambad)))
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fmt.Printf("accuracy: %.6f\n", float64(nhamok+nspamok)/float64(nhamok+nhambad+nspamok+nspambad))
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}
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func cmdJunkPlay(c *cmd) {
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c.unlisted = true
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c.params = "hamdir spamdir"
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c.help = "Play messages from ham and spam directory according to their time of arrival and report on junk filter performance."
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a := junkFlags(c.flag)
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args := c.Parse()
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if len(args) != 2 {
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c.Usage()
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}
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defer a.Profile()()
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a.SetLogLevel()
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f := must(junk.NewFilter(mlog.New("junkplay"), a.params, a.databasePath, a.bloomfilterPath))
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defer f.Close()
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// We'll go through all emails to find their dates.
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type msg struct {
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dir, filename string
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ham, sent bool
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t time.Time
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}
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var msgs []msg
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var nbad, nnodate, nham, nspam, nsent int
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scanDir := func(dir string, ham, sent bool) {
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for _, name := range listDir(dir) {
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path := dir + "/" + name
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mf, err := os.Open(path)
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xcheckf(err, "open %q", path)
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fi, err := mf.Stat()
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xcheckf(err, "stat %q", path)
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p, err := message.EnsurePart(mf, fi.Size())
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if err != nil {
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nbad++
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mf.Close()
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continue
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}
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if p.Envelope.Date.IsZero() {
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nnodate++
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mf.Close()
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continue
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}
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mf.Close()
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msgs = append(msgs, msg{dir, name, ham, sent, p.Envelope.Date})
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if sent {
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nsent++
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} else if ham {
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nham++
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} else {
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nspam++
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}
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}
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}
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hamDir := args[0]
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spamDir := args[1]
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scanDir(hamDir, true, false)
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scanDir(spamDir, false, false)
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if a.sentDir != "" {
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scanDir(a.sentDir, true, true)
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}
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// Sort the messages, earliest first.
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sort.Slice(msgs, func(i, j int) bool {
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return msgs[i].t.Before(msgs[j].t)
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})
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// Play all messages as if they are coming in. We predict their spaminess, check if
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// we are right. And we train the system with the result.
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var nhamok, nhambad, nspamok, nspambad int
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play := func(msg msg) {
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var words map[string]struct{}
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path := msg.dir + "/" + msg.filename
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if !msg.sent {
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var prob float64
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var err error
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prob, words, _, _, err = f.ClassifyMessagePath(path)
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if err != nil {
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nbad++
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return
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}
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if msg.ham {
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if prob < a.spamThreshold {
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nhamok++
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} else {
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nhambad++
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}
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} else {
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if prob > a.spamThreshold {
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nspamok++
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} else {
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nspambad++
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}
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}
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} else {
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mf, err := os.Open(path)
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xcheckf(err, "open %q", path)
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defer mf.Close()
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fi, err := mf.Stat()
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xcheckf(err, "stat %q", path)
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p, err := message.EnsurePart(mf, fi.Size())
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if err != nil {
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log.Printf("bad sent message %q: %s", path, err)
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return
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}
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words, err = f.ParseMessage(p)
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if err != nil {
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log.Printf("bad sent message %q: %s", path, err)
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return
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}
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}
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if err := f.Train(msg.ham, words); err != nil {
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log.Printf("train: %s", err)
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}
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}
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for _, m := range msgs {
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play(m)
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}
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err := f.Save()
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xcheckf(err, "saving filter")
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fmt.Printf("completed, nham %d, nsent %d, nspam %d, nbad %d, nwithoutdate %d\n", nham, nsent, nspam, nbad, nnodate)
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fmt.Printf("total ham, ok %d, bad %d\n", nhamok, nhambad)
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fmt.Printf("total spam, ok %d, bad %d\n", nspamok, nspambad)
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fmt.Printf("specifity (true negatives, hams identified): %.6f\n", float64(nhamok)/(float64(nhamok+nhambad)))
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fmt.Printf("sensitivity (true positives, spams identified): %.6f\n", float64(nspamok)/(float64(nspamok+nspambad)))
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fmt.Printf("accuracy: %.6f\n", float64(nhamok+nspamok)/float64(nhamok+nhambad+nspamok+nspambad))
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}
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