Naive Bayes Classifiers
Naive Bayes mai sauri ne, mai rarrafe mai yuwuwa wanda aka gina akan ka'idar Bayes wanda ke ɗaukan kowane fasali mai zaman kansa idan aka ba aji.
Dubawa
Despite that unrealistic assumption, it works remarkably well for text tasks like spam filtering.
Zurfafa nutsewa
Naive Bayes yana juya rarrabuwa zuwa lissafin yiwuwar. Yin amfani da ka'idar Bayes, yana ƙididdige yuwuwar aji da aka ba da sifofin shigarwa, sannan ta ɗauki ajin tare da mafi girman maki. Bangaren 'rashin hankali' shine tunaninsa cewa duk fasalulluka sun kasance masu zaman kansu idan aka yi la'akari da aji, don haka zai iya ninka yiwuwar fasalin mutum ɗaya maimakon yin ƙirar mu'amalarsu. Wannan yana rage yawan bayanai da ƙididdiga da ake buƙata. Bambance-bambancen gama gari sun haɗa da Multinomial Naive Bayes (ƙididdigar kalmomi a cikin takardu), Bernoulli Naive Bayes (kalmar da ke nan/ba ta nan), da Gaussian Naive Bayes (fasalolin ci gaba waɗanda aka tsara tare da rarraba ta al'ada). Yana horarwa a cikin wucewa guda ɗaya akan bayanan, yana buƙatar ɗan daidaitawa, kuma yana sarrafa dubunnan fasali cikin alheri, wanda ya mai da shi babban tushe don gano spam da rarraba takardu.
Fahimtar Fasaha
Don ajin c da fasali x1..xn, yana lissafta lokutan P(c) samfurin P(xi|c), sannan ya daidaita. Saboda ninka ƙananan yuwuwar da yawa yana haifar da raguwar lamba, aiwatar da jimlar yuwuwar log maimakon. Laplace (ƙara-ɗaya) smoothing yana hana kalma ɗaya da ba a gani daga sifilin fitar da samfuran gaba ɗaya. Ana ƙididdige yiwuwar P(xi|c) da P(c) na gaba ta hanyar ƙididdige sauƙi daga tsarin horo, wanda shine dalilin da ya sa horo shine ainihin ƙididdige mitoci.
Dabarun Tasiri
Shawarwari masu haske
Yana taimaka muku keɓance bayyanannen da'awar fasaha daga harshen talla.
Kudin da kasafin kuɗi
Kuna iya yin mafi kyawun tambayoyin aiwatarwa kafin kashe kuɗi ko lokaci.
Ƙungiya da aikin aiki
Ƙungiyoyin da ke da fahimtar juna suna yin mafi kyawun samfura, manufofi, da yanke shawara na koyo.
Makomar Naive Bayes Classifiers
Cibiyoyin sadarwa masu zurfi da taswira yanzu sun mamaye rarrabuwar rubutu, don haka Naive Bayes ba kasafai ne ke kan gaba ba. Amma yana dawwama a matsayin tushe mai ƙarfi, kusa-kusa, kayan aikin koyarwa da za'a iya fassarawa, da zaɓi mai amfani lokacin da bayanai ba su da yawa, latency dole ne ƙarami, ko ƙididdige ƙididdigewa. Yi tsammanin ya kasance cikin manne a cikin matattara masu nauyi akan na'ura, bututun samfur mai sauri, da tsarin gauraye inda mai rahusa mai rahusa ta farko ke shigar da hanyoyin shiga kafin a kira samfurin mafi nauyi.
Aiwatar da Gaskiyar Duniya
Imel tace spam na imel wanda ke ƙididdige saƙon ta kalmomin da suka ƙunshi
Binciken jin ra'ayi mai yiwa samfur alama mai inganci ko mara kyau
Gudanar da tikitin tallafi ko labaran labarai cikin nau'ikan jigo
Gano harshe da sassauƙar rarrabuwa a cikin bututun bincike
Hatsari & Tsare-tsare
Ƙungiyoyi daban-daban na iya amfani da kalmar iri ɗaya daban, don haka ayyana iyaka da wuri.
Alamomi na iya yin kama da ƙarfi yayin da aikin zahirin duniya bai yi daidai ba.
Yin watsi da ingancin bayanai da tsare-tsaren kimantawa galibi yana haifar da sakamako mara ƙarfi.
Taswirar Hanya
Fara da ma'anar harshe a sarari na sakamakon da kuke buƙata.
Zaɓi ma'aunin nasara ɗaya da yanayin gazawa ɗaya kafin gwaji.
Gudun ƙaramin matukin jirgi tare da bayanan wakilci, ba saitin demo da aka goge ba.
Takaddun inda Naive Bayes Classifiers ke taimakawa kuma inda mafi sauƙi hanyoyin suka fi kyau.
Ci gaba da Bincike
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Jagora na gaba
Ƙididdigar Haɗarin Bayes mafi ƙarancin
Tambayoyin da ake yawan yi
What is Naive Bayes Classifiers?
Naive Bayes mai sauri ne, mai rarrafe mai yuwuwa wanda aka gina akan ka'idar Bayes wanda ke ɗaukan kowane fasali mai zaman kansa idan aka ba aji. Duk da wannan zato mara gaskiya, yana aiki da kyau sosai don ayyukan rubutu kamar tace spam.
Menene ainihin zato 'naive' a cikin Naive Bayes classifier?
Samfurin yana ɗaukar kowane fasalin yana ba da gudummawa da kansa ga sakamakon da aka ba ajin, yana barin shi ninka yuwuwar kowane fasali.
Wanne ka'ida aka gina Naive Bayes?
Yana amfani da ka'idar Bayes don canza yuwuwar aji na farko da fasalin fasalin zuwa yuwuwar gaba ga kowane aji.
Me yasa aiwatarwa yawanci ke tattara abubuwan yuwuwar log-maimakon ninka danye yiwuwar?
Ƙara yawan yuwuwar da ke ƙasa da 1 na iya rikiɗawa zuwa sifili, don haka ɗaukar rajistan ayyukan da tattara bayanai yana sa lissafin ya tsaya tsayin daka.
Wace matsala Laplace (ƙara-daya) smoothing ke magance?
Ba tare da santsi ba, kalmar da ba a taɓa gani tare da aji tana ba wa wannan ajin yuwuwar sifili; kirga-daya ku guje wa wannan.
Wane bambance-bambancen Naive Bayes ya fi halitta don fasalulluka-ƙididdigar kalmomi a cikin takardu?
Multinomial Naive Bayes ƙirar ƙididdiga masu hankali kamar sau nawa kowace kalma ta bayyana, suna mai da ta daidaitaccen rubutu.