MUHIMMAN JAGORA

Rage Girman Girma

Rage girman girman yana raguwa bayanai daga ginshiƙai da yawa (fasali) ƙasa zuwa kaɗan yayin kiyaye mahimman tsari.

2 min karatuAn sabunta ta ƙarshe

Dubawa

It fights the 'curse of dimensionality,' speeds up models, and lets you actually visualize complex data in 2D or 3D.

Zurfafa nutsewa

Rubutun bayanan gaskiya galibi suna da ɗaruruwa ko dubbai na fasali: kowane pixel a cikin hoto, kowace kalma a cikin ƙamus, kowane firikwensin akan na'ura. A cikin irin waɗannan wurare masu girman girman, wuraren bayanai sun zama marasa ƙarfi kuma suna da nisa, ma'aunin nesa ba su da tabbas, kuma ƙira suna yin wuce gona da iri. Wannan shi ne la'anar girma. Rage girman taswirorin bayanan zuwa ƙananan girma yayin kiyaye alaƙa mai ma'ana. PCA na yin haka ne a layi daya ta hanyar nemo kwatance mafi girman bambance-bambance. t-SNE da UMAP ba na kan layi ba ne kuma sun yi fice wajen bayyana tari don gani. Rage girma yana kawar da fasali mai yawa ko hayaniya, yana yanke ƙwaƙwalwar ajiya da ƙididdigewa, kuma akai-akai yana inganta daidaiton ƙirar ƙasa saboda akwai ƙarancin siginar da bai dace ba don rikitar da shi.

Fahimtar Fasaha

PCA tana aiki ne ta hanyar ƙididdige daidaituwar sifofin da gano eigenvectors, 'manyan abubuwan da aka gyara,' waɗanda ke nuni tare da mafi girman bambance-bambance. Kuna adana manyan ƴan abubuwan da aka haɗa da bayanan aiwatarwa akan su, kuna watsar da ƙananan bambance-bambancen kwatance waɗanda galibi su ne hayaniya. t-SNE da UMAP a maimakon su ƙirƙiri alaƙar maƙwabta: suna ƙoƙarin kiyaye maki waɗanda ke kusa da babban girma kusa a cikin taswirar ƙasan ƙasa. UMAP tana gina jadawali na maki kusa, wanda ke sa shi sauri fiye da t-SNE kuma ya fi kyau a adana tsarin duniya mai faɗi.

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 Rage Dimensionality

Rage girma yanzu mataki ne na yau da kullun a cikin manyan bututun AI maimakon aiki na tsaye. UMAP ya zama tsoho don bincika abubuwan haɗawa daga manyan harshe da ƙirar hangen nesa, inda injiniyoyi ke aiwatar da dubban girma cikin taswirar 2D don bincika abin da ƙirar ta koya. Yi tsammanin haɗin kai tare da dashboards masu ma'amala, saurin aiwatarwa-GPU mai saurin aiwatarwa don saiti-jeri biliyan, da haɓaka amfani a cikin aikin fassara, inda masu bincike ke rage ƙirar ƙira ta ciki don fahimta da gyara halayensa.

Aiwatar da Gaskiyar Duniya

Ƙirƙirar kalma ko jumlar jumla daga ƙirar harshe a cikin 2D tare da UMAP don ganin waɗanne dabaru ƙungiyoyin samfuri tare.

Matsa dubunnan ma'auni-bayanin halitta ga kowane majiyyaci zuwa wasu ƴan abubuwa kafin tara nau'ikan cututtuka

Rage fasalulluka na hoto kafin ciyar da su zuwa mai ƙira don haka horarwa yana da sauri kuma ba ta da saurin wuce gona da iri

Haɓaka halayen abokin ciniki a cikin ɗaruruwan ma'auni azaman shirin watsawa na 2D don tabo ɓangarori na kasuwa

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

1

Fara da ma'anar harshe a sarari na sakamakon da kuke buƙata.

2

Zaɓi ma'aunin nasara ɗaya da yanayin gazawa ɗaya kafin gwaji.

3

Gudun ƙaramin matukin jirgi tare da bayanan wakilci, ba saitin demo da aka goge ba.

4

Daftarin aiki inda Rage Girman Girma yana taimakawa kuma inda hanyoyin mafi sauƙi suka fi kyau.

Ci gaba da Bincike

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Jagora na gaba

Barlow Twins and Redundancy Rage

Tambayoyin da ake yawan yi

What is Dimensionality Reduction?

Rage girman girman yana raguwa bayanai daga ginshiƙai da yawa (fasali) ƙasa zuwa kaɗan yayin kiyaye mahimman tsari. Yana yaƙi da 'la'anar girma,' yana haɓaka ƙirar ƙira, kuma yana ba ku damar haƙiƙa haƙiƙanin bayanai masu rikitarwa a cikin 2D ko 3D.

Menene 'la'anar girma'?

A cikin wurare masu girman gaske, maki sun bazu nesa da nisa kuma matakan nesa suna rushewa, don haka samfuran suna kokawa don nemo alamu kuma suna iya wuce gona da iri.

Ta yaya PCA ke yanke shawarar waɗanne kwatance don kiyayewa?

PCA na samo manyan abubuwan da aka gyara, gatura na mafi girman bambance-bambance, kuma suna kiyaye na sama saboda suna ɗaukar mafi yawan bayanai.

Me yasa ake kiran PCA hanyar 'Linear'?

Kowane babban sashi haɗin kai ne na asali na asali, don haka PCA ba zai iya ɗaukar lanƙwasa, tsarin da ba na kan layi ba kamar yadda t-SNE ko UMAP za su iya.

Menene t-SNE da UMAP musamman masu kyau?

Dukansu fasahohin da ba na kan layi ba ne waɗanda ke ajiye maki kusa kusa a cikin taswirar ƙasan ƙasa, suna sa gungu ganuwa a cikin 2D ko 3D.