 Monisá likanisi oyo epesami na ndakisa
Apprentissage supervisée ezali méthode ya apprentissage machine esika algorithme e former na ensemble ya ba données étiqueté, esika sortie oyo elingi eyebani déjà. Algorithme eyekolaka relation entre ba fonctionnalités ya entrée na ba étiquettes ya sortie pona kosala ba prédictions pona ba données ya sika, oyo emonanaka te. Ndakisa ya boyekoli oyo etambwisami ekoki komonana na filtrage ya ba spam ya email. Toloba ete ozali na liboke monene ya ba email, mosusu na yango ezali na elembo lokola spam mpe mosusu lokola spam te. Ba emails esalaka lokola ba données ya entrée mpe ba étiquettes ya spam/pasm te esalaka lokola ba étiquettes ya sortie. Algorithme ya apprentissage supervisée, lokola classificateur Naive Bayes, ekoki kozala formation na ba données oyo ya email oyo ezali na étiquette mpo na koyekola bizaleli ya ba emails ya spam mpe ya ba email ya spam te. Sima ya formation, algorithme ekoki sima ko prédire soki email ya sika, oyo ekoya ekoki kozala spam to te. Na ndakisa oyo, algorithme ezwaki formasyo na ba données étiquetées na ndenge ya supervisée mpe ekoki kosala ba prédictions ya sikisiki na ba emails ya sika, ko filtrer efficacement ba emails ya spam.