Goyan bayan Injinan Vector
Injin vector mai goyan baya (SVM) wani al'adar algorithm ne wanda ke raba ƙungiyoyi biyu ta zana iyakoki mafi faɗi a tsakanin su.
Dubawa
It was one of the most powerful classifiers before deep learning and is still strong on small, clean datasets.
Zurfafa nutsewa
Wani SVM yana gano iyakar yanke shawara, wanda ake kira hyperplane, wanda ke ƙara girman gefe, rata tsakanin iyaka da wuraren bayanai mafi kusa na kowane aji. Waɗancan wuraren mafi kusa su ne 'hanyoyin tallafi,' kuma su kaɗai ne ke ayyana iyaka, wanda ke sa ƙirar ta zama mai ƙarfi da juriya ga masu nesa da nesa. Lokacin da ba za a iya raba bayanai ta hanyar madaidaiciyar layi ba, dabarar kernel ta zana shi zuwa wani wuri mafi girma inda tsaftataccen rabuwa ke wanzu, ba tare da taɓa lissafta waɗannan haɗin kai kai tsaye ba. Matsakaicin gefe mai laushi yana ba da damar wasu ɓarna, wanda ma'auni C ke sarrafa shi, don haka ƙirar tana daidaita faffadan tazara akan kurakuran horo. SVMs sun yi fice lokacin da fasali suna da yawa amma misalai kaɗan ne, kamar a cikin rarrabuwar rubutu da bioinformatics.
Fahimtar Fasaha
Mahimmancin gefe matsala ce ta ingantawa, don haka SVMs suna da mafi kyawun duniya guda ɗaya, sabanin hanyoyin sadarwa na jijiyoyi. Dabarar kwaya tana maye gurbin samfuran dige tsakanin maki bayanai tare da aikin kwaya, kamar aikin tushen radial (RBF) ko kwaya mai yawa, wanda ke ƙididdige kamanni a cikin sarari mai girma a fakaice. Wannan yana barin hanyar layi ta zana iyakoki masu lankwasa da rahusa. Matsakaicin hyperparameters guda biyu sun mamaye kunnawa: C, wanda ke cinikin nesa da nisa akan kurakurai, da gamma a cikin kwaya ta RBF, wanda ke saita nisan tasirin kowane batu.
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 Tallafin Injinan Vector
SVMs an mamaye su ta hanyar zurfafan koyo da bishiyun da aka haɓaka don manyan, hadaddun bayanai, amma sun kasance zaɓi mai dogaro lokacin da bayanai ke da ƙarancin girma, girma, ko buƙatar tushe mai ƙarfi, ingantaccen fahimta. Suna zama gama gari a cikin koyarwa, a cikin bioinformatics da ayyukan rubutu, da kuma a cikin iyakantattun saitunan albarkatu inda ƙaramin, ƙirar sauri ke bugun cibiyar sadarwa mai nauyi. Yi tsammanin SVMs za su dawwama azaman ingantaccen kayan aiki na gargajiya da ma'auni maimakon iyakar sabon bincike.
Aiwatar da Gaskiyar Duniya
Rubutun rubutu da spam, inda takaddun ke da dubban fasalulluka na kalmomi amma ƙayyadaddun misalai.
Rarraba hotuna a kan ƙananan bayanan bayanai kafin zurfin ilmantarwa ya zama rinjaye.
Ciwon daji da rarrabuwa-bayanin halitta a cikin bioinformatics tare da fasali da yawa da ƴan samfurori.
Gane lambar lambobi da aka rubuta da hannu, babban ma'aunin SVM akan saitin bayanan MNIST.
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 Injin Tallafin Vector ke taimakawa kuma inda hanyoyin mafi sauƙi suka fi kyau.
Ci gaba da Bincike
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Jagora na gaba
Tushen Koyon Inji
Tambayoyin da ake yawan yi
What is Support Vector Machines?
Injin vector mai goyan baya (SVM) wani al'adar algorithm ne wanda ke raba ƙungiyoyi biyu ta zana iyakoki mafi faɗi a tsakanin su. Ya kasance ɗaya daga cikin mafi ƙarfi masu rarrabawa kafin zurfin koyo kuma har yanzu yana da ƙarfi akan ƙanana, tsaftataccen matattun bayanai.
Menene na'ura mai tallafawa vector ke ƙoƙarin haɓakawa?
Wani SVM yana nemo babban jirgin sama wanda ke ƙara girman gefe, nisa zuwa mafi kusancin wurare na kowane aji, don mafi girman rabuwa.
Menene 'masu goyon baya' a cikin SVM?
Sai kawai maki mafi kusa da iyaka, masu ba da tallafi, sun ƙayyade hyperplane; sauran maki na iya motsawa ba tare da canza shi ba.
Wace matsala dabarar kwaya ke magance?
Dabarar kernel ta fito da taswirori a fakaice zuwa sararin sararin samaniya mai girma inda madaidaicin iyaka ke aiki, yana ba da damar rarrabuwar kawuna cikin arha.
Menene siga C ke sarrafawa a cikin SVM mai laushi mai laushi?
C yana daidaita samun babban tazara akan bada izinin wasu kurakuran horo; ƙarami C na nufin faffaɗa, mafi girman juriya.
Wanne kwaya aka fi amfani dashi don ƙirƙirar iyakoki masu sassauƙa, masu lanƙwasa?
RBF (Gaussian) kwaya sanannen tsoho ne wanda ke auna kamanni bisa nisa, yana ba da damar iyakoki mara kyau.